فهرست مطالب
مجله مهندسی صنایع و مدیریت شریف
سال بیست و هفتم شماره 1 (پاییز و زمستان 1390)
- 154 صفحه، بهای روی جلد: 70,000ريال
- تاریخ انتشار: 1390/09/01
- تعداد عناوین: 14
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- مقالات پژوهشی
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صفحه 3ورود سازمان ها به اقتصاد دانش محور، نقش سرمایه های انسانی و اجتماعی در دو بعد فردی و سازمانی از اهمیت ویژه یی برخوردار شده است، به طوری که بسیاری از سازمان ها از آن به عنوان نیروی محرکه ی مهم و تاثیرگذار در ایجاد مزیت رقابتی پایدار یاد می کنند. از این رو مدیریت و بهره گیری صحیح از آن می تواند پیامدهای مطلوبی در سطوح فردی و سازمانی به همراه داشته باشد. از آنجا که تاکنون اکثر تحقیقات بر پیامدهای سطح سازمانی مدیریت سرمایه ی انسانی و اجتماعی متمرکز شده اند، در نوشتار حاضر تاثیرگذاری مدیریت سرمایه ی انسانی و اجتماعی با لحاظ کردن نقش تعدیل کنندگی ادراک از حمایت سازمانی بر موفقیت شغلی مدیران عملیاتی در بانک ملت مورد بررسی قرار گرفته است. روش تحقیق مورد استفاده پیمایشی همبستگی و به طور مشخص مبتنی بر مدل تحلیل رگرسیون سلسله مراتبی است. نتایج تحقیق حاضر نشان داد که متغیرهای موصوف طبق مدل ارائه شده بر موفقیت شغلی مدیران تاثیر می گذارند.
کلیدواژگان: سرمایه ی انسانی، سرمایه ی اجتماعی، حمایت سازمانی، موفقیت شغلی -
صفحه 11مسئله ی مکان یابی مراکز قطبیپانویس{H U B l o c a t i o n p r o b l e m} کاربرد وسیعی در دنیای واقعی ازجمله در شبکه های ارتباطات، پستی، سیستم های حمل ونقل و خطوط هوایی دارد و تحقیقات زیادی درخصوص آن انجام شده است. این مسئله به ویژه در وضعیت هایی که شدت جریان بالایی بین یک سری نقاط مبدا و مقصد در یک شبکه وجود دارد، کاربرد پیدا می کند.
در این حالت به جای ارتباط مستقیم بین این نقاط سعی می شود با انتخاب تعدادی از این نقاط به عنوان مراکز قطبی، جریان ها از طریق این مراکز عبور داده شوند تا از صرفه جویی های مربوطه استفاده شود. بنابراین هدف مسئله انتخاب برخی گره ها به عنوان مرکز قطبی و تخصیص گره های غیرقطبی به این مراکز، به منظور دست یابی به کم ترین هزینه برای شبکه است. در بیشتر تحقیقات انجام شده در این حوزه، سیستم از نقطه نظر برآورده شدن کم ترین هزینه مورد بررسی قرار گرفته، در حالی که زماننیز عامل مهمی است که باید به عنوان یک هدف منظور شود. همچنین، مطالعات محدود به حالاتی قطعی از شدت جریان بوده است. در این تحقیق سعی شده این مدل ها در حالت دوهدفه)زمان انتظار و هزینه(و حالت های غیرقطعی)فازی(از پارامترهای شدت جریان بررسی شود. از نظریه ی برنامه ریزی فازی به منظور تخمین توابع هدف فازی، و از یک الگوریتم ترکیبی هوشمند فراابتکاری)متاهیوریستیک(برای حل مدل توسعه یافته بهره گرفته شده است.
کلیدواژگان: مکان یابی مراکز قطبی، نظریه ی صف، برنامه ریزی فازی، شبیه سازی فازی، الگوریتم هوشمند فراابتکاری، شبیه سازی تبرید -
صفحه 21در این نوشتار با ارزیابی مدل های مختلف و با اتکا بر مطالعات تطبیقی و تحلیل اطلاعات حاصل از مطالعات ملی و نیز نتایج نظرسنجی از خبرگان، چارچوب مفهومی جامعی متشکل از سه بعد آمادگی شامل: «آمادگی سخت»، «آمادگی نرم»، «آمادگی نظارت، هماهنگی و پشتیبانی» برای ارزیابی آمادگی الکترونیکی در دانشگاه های کشور طراحی شده است. علاوه بر این با تبیین ارکان مختلف هریک از این ابعاد در مجموع چهارده شاخص اصلی شامل: سیاست آموزشی، مدیریت، استاندارد، محتوا، قوانین و مقررات، منابع مالی، منابع انسانی، فرهنگ، امنیت، تجهیزات سخت افزاری، شبکه ی ارتباطی، و بالاخره نظارت، هماهنگی، و پشتیبانی برای این ابعاد شناسایی شد. نکته ی مهم در طراحی این مدل، تاکید بر این نکته است که از دید صاحب نظران و خبرگان عرصه ی آموزش عالی و یادگیری الکترونیکی، حرکت به سمت تحقق دانشگاه مجازی در ایران مستلزم توجه همه جانبه به تمامی وجوه منشور پیش گفته است. از این رو ضمن بیان روند استخراج این مدل بومی، وزن هریک از شاخص ها و نشان گرهای مدل نیز تعیین شده است تا علاوه بر ارائه ی چارچوبی مفهومی، معیاری کمی برای اندازه گیری وضعیت دانشگاه های موجود در عرصه ی یادگیری الکترونیکی نیز تبیین شود. در پایان این نوشتار پیشنهادهایی برای کاربرد این مدل در دانشگاه های کشور ارائه شده است.
کلیدواژگان: فناوری اطلاعات، آمادگی الکترونیکی، یادگیری الکترونیکی، دانشگاه، مدل ارزیابی، ایران -
صفحه 31در این نوشتار با ارائه ی نمونه ی عملی فرایند «افشانه ی خشک کنندهپانویس{s p r a y d r y i n g}»، مدل سازی فرایندها با استفاده از مدل های رگرسیون لجستیک و الگوریتم شبکه ی عصبی مصنوعی با هدف پیش بینی)برون یابی و درون یابی(عملکرد فرایند به کار گرفته می شود. به منظور مقایسه ی قدرت هرکدام از این دو مدل در پیش بینی عملکرد فرایند، شاخص های ارزیابی پایایی مدل، شامل ضرایب تعیین مدل و درصد صحت پیش بینی، محاسبه و تحلیل می شوند. استفاده از شبکه ی عصبی مصنوعی در این نوشتار، به منظور معماری مدل شبکه ی عصبی فرایند «افشانه ی خشک کننده» با اتخاذ یک رویکرد عمومی و انتخاب الگوریتم پس انتشار خطا به کمک داده های مستقیم صورت می گیرد. پس از حصول اطمینان از برتری مدل شبکه ی عصبی فرایند نسبتبه مدل لجستیک آن و با توجه به نتایج ارزیابی پایایی، سناریوهای مختلفی برای تنظیم ورودی های با توجه به عملکرد پیش بینی شده توسط مدل شبکه ی عصبی فرایند طراحی می شود که با استفاده از آن می توان کنترل پیش بینانه ی عملکرد فرایند را جایگزین روش های مبتنی بر سعی و خطا برای کنترل عملکرد فرایند کرد.
کلیدواژگان: پیش بینی عملکرد شبکه ی عصبی مصنوعی، مدل سازی، رگرسیون لجستیک، افشانه ی خشک کننده (اسپری درایینگ) -
صفحه 39پژوهش حاضر مطالعه یی کاربردی درمورد ارزیابی صلاحیت سازندگان تجهیزات صنعت نفت است. با توجه به پیچیده ترشدن شرایط رقابت جهانی، امروزه به مرور ارزیابی های سنتی جای خود را به فرایندهای ارزیابی علمی و تخصصی داده است. افزون براین، به دلیل اهمیت فراوان صنعت نفت در کشور ما، پرداختن به ارزیابی همه ی سازندگان تجهیزات بسیار ضروری به نظر می رسد. در این تحقیق 9 شاخص برای ارزیابی سازندگان تجهیزات صنعت نفت تشخیص داده شده، و با استفاده از روش P R O M S O R T شرکت ها به چهار گروه شرکت های عالی، خوب، متوسط و ضعیف طبقه بندی شده اند.
کلیدواژگان: PROMSORT، PROMETHEE، ارزیابی، سازندگان تجهیزات صنعتی -
صفحه 47در این نوشتار یک سیستم تولید انبارش چندمحصولی در دو حالت ظرفیت تولید نامحدود و محدود، با تقاضا و زمان تولید تصادفی در نظر گرفته شده است. هدف یافتن شرایط بهینه در انتخاب حالت ساخت برای سفارش)M T O(پانویس{m a k e t o o r d e r} یا ساخت برای انبارش)M T S(پانویس{m a k e t o s t o c k} برای هریک از محصولات، با کمینه سازی مجموع هزینه های نگه داری و کمبود موجودی است. فرضیات جدیدی که منطبق با شرایط دنیای واقعی در نظر گرفته شده اند عبارت اند از: امکان تولید محصولات معیوب با بازرسی بدون تاخیر، تولید محصولات معیوب همراه با بازرسی تاخیردار. همچنین سیستم تک مرحله یی را به حالت تولید چندمرحله یی به صورت شبکه یی از ماشین آلات تعمیم داده ایم. هریک از مسائل مورد بررسی با کمک سیستم های صف مدل سازی شده و با استخراج پارامترهای لازم، نسبت به استخراج شرایط بهینه ی ساخت برای سفارش و ساخت برای انبارش اقدام شده است.
کلیدواژگان: سیستم تولید انبارش، ساخت برای سفارش، ساخت برای انبارش، نظریه ی صف، هزینه ی موجودی، هزینه ی کمبود -
صفحه 55در دهه ی گذشته «دفتر مدیریت پروژه» نقش برجسته یی در بسیاری از سازمان های پروژه محور ایفا کرده است، اما به رغم افزایش تعداد این دفاتر، درک شفافی از موجودیت و کارکردهای آن وجود ندارد. هدف این تحقیق پیمایشی، شناسایی موجودیت دفتر مدیریت پروژه» در سازمان های بزرگ مهندسی و ساخت صنایع نفت، گاز و پتروشیمی ایران)9 شرکت بزرگ(است، و ضمن آن موجودیت، زمان پیدایش، تعداد پروژه های در حیطه ی اختیار، میزان اختیارات، کارکردهای دفتر مدیریت پروژه، دلایل پیاده سازی و چالش های پیاده سازی دفتر مدیریت پروژه بررسی و تحلیل می شود. روش تحقیق مبتنی بر جمع آوری اطلاعات از طریق پرسش نامه است. براساس نتایج به دست آمده، دفتر مدیریت پروژه در سازمان های مورد بحث موضوعی جدید است تا آنجا که بیش از 60٪ دفاتر مدیریت پروژه در سه سال اخیر ایجاد شده اند. کارکردهایی مانند کنترل و نظارت بر عملکرد پروژه ها، ابزارهای نرم افزاری مدیریت پروژه و ایجاد متدولوژی استاندارد مدیریت پروژه، بیشترین کاربرد را در سازمان های موضوع تحقیق دارند. دست یابی به اهداف «مثلث سه گانه ی طلایی پروژه» یعنی زمان، هزینه، عملکرد/کیفیت از بالاترین اولویت در میان دلایل پیاده سازی برخوردار است. بزرگ ترین چالش پیاده سازی دفتر مدیریت پروژه، ریسک های تغییر فرهنگ سازمانی و پس از آن کمبود منابع انسانی حرفه یی در مدیریت پروژه است.
کلیدواژگان: دفتر مدیریت پروژه، صنعت ساخت، صنعت نفت گاز و پتروشیمی -
صفحه 65با گسترش روزافزون تمرکز سازمان ها در توسعه ی سیستم های مدیریت راهبردی، تعریف و پیاده سازی روش های کارای ارزیابی عملکرد به عنوان ابزار قدرت مند افزایش مزیت رقابتی سازمان ها شناخته شده است. یکی از برجسته ترین روش های ارزیابی عملکرد، الگوی کارت امتیازی متوازنپانویس{b a l a n c e d s c o r e c a r d (B S C)} است. از ویژگی هایی که در پیاده سازی الگوی کارت امتیازی متوازن طی چند سال اخیر، مورد توجه پژوهشگران قرار گرفته است، تعیین اولویت و وزن دهی شاخص های کلیدی عملکرد در این الگو است. در این نوشتار از مدلی برای رتبه بندی شاخص های کلیدی عملکرد با تلفیق الگوی کارت امتیازی متوازن و روش فرایند تحلیل شبکه فازی استفاده شده است. نتایج پیاده سازی این مدل در یکی از سازمان های وابسته به شهرداری اصفهان نشان می دهد؛ به دلیل توجه به وابستگی بین مولفه های هم سطح و نیز وجود رابطه های بازگشتی بین اهداف و راهکارها درنقشه ی استراتژی و نیز ابهام زدایی ناشی از وزن دهی غیرفازی، اوزان به دست آمده با مدل ذهنی تصمیم گیران ارشد سازمان، تناسب کامل دارد و ملاک مناسبی برای تخصیص منابع است.
کلیدواژگان: سیستم مدیریت راهبردی، کارت امتیازی متوازن، وزن دهی و اولویت بندی، فرایند تحلیل سلسله مراتبی، فرایند تحلیل شبکه یی فازی -
صفحه 75در این تحقیق مسئله ی زمان بندی گروهی در محیط جریان کارگاهی)فلوشاپ(انعطاف پذیر، با در نظر گرفتن زمان های آماده سازی وابسته به توالی گروه ها و نیز تابع هدف کمینه سازی زمان تکمیل مورد نیاز برای پردازش کارهای داخل گروه ها)$F F_m|f m l s، S_{p l c}|C_{m a x}$(مورد بررسی قرار گرفته است. برای این مسئله یک مدل برنامه ریزی خطی عدد صحیح مختلط برای نخستین بار ارائه شده است. دو رویکرد فراابتکاری بر پایه ی شبیه سازی تبرید برای حل تقریبی مسئله توسعه داده شده است. مقایسه ی عملکرد الگوریتم های پیشنهادی در این تحقیق با دیگرالگوریتم موجود در ادبیات که برمبنای جست وجوی ممنوع استٓ نشان می دهد که الگوریتم شبیه سازی تبرید پیشنهادی به طور متوسط جواب ها را حدود 3 درصد بهبود می دهد.
کلیدواژگان: زمان بندی گروهی وابسته به توالی، جریان کارگاهی انعطاف پذیر_ روش های فراابتکاری، شبیه سازی تبرید، مدل سازی ریاضی -
صفحه 93در این نوشتار دو مدل استوار برای مسائل بهینه سازی سبد مالی دارای اختیار معامله توسعه داده می شود. در مدل اول با توجه به رابطه ی غیرخطی)شکسته ی خطی(بین داده های غیرقطعی)ارزش سهام و اختیار معامله(، یک مدل همتای استوار بیش محافظه کارانه ارائه می دهیم؛ در مدل دوم نیز با روشی متفاوت همتای استوار با درجه محافظه کاری قابل کنترل ارائه می شود. خصوصیت اصلی مدل های استوار ارائه شده در این پژوهش، نحوه ی برخورد آن ها با روابط غیرخطی پارامترهای دارای عدم قطعیت در مدل است. برای تحلیل دو مدل مذکور سه مسئله با تعداد 100 نوع سهام و حدود 400 اختیار معامله حل شده و نتایج آن مورد بررسی قرار می گیرد.
کلیدواژگان: بهینه سازی سبد مالی، اختیار معامله، بهینه سازی استوار -
صفحه 103در استراتژی نگه داری و تعمیر مبتنی بر شرایط دستگاه)C B M(پانویس{c o n d i t i o n-b a s e d m a i n t e n a n c e (C B M)}، هدف این است که با انجام بازرسی های دوره یی و کنترل شرایط دستگاه به عمر واقعی تعویض نزدیک شود. تحقیقات متعددی درخصوص لحاظ تبعات اقتصادی تصمیمات در استراتژی C B M صورت گرفته است. از جمله این تحقیقات، روش حد کنترل است که در آن نرخ توام نرخ خرابی دستگاهپانویس{h a z a r d r a t e} و تاثیر مقادیر متغیرهای کنترل شرایطپانویس{c o v a r i a t e s}،با استفاده از مدل تلفیقی نرخ خرابی P H M پانویس{p r o p o r t i o n a l h a z a r d s m o d e l (P H M)}، و با توجه به سوابق اطلاعاتی دستگاه، تخمین زده می شود. سپس، با لحاظ هزینه های تعویض، بهترین حد کنترل به گونه یی که متوسط هزینه های مذکور در یک دوره ی طولانی کمینه شود، تعیین می شود. در مدل ارائه شده در نوشتار حاضر، علاوه بر لحاظ هزینه های تعویض در تعیین حد کنترل بهینه، هزینه انجام بازرسی ها نیز در نظر گرفته شده است تا بتوان بهترین فواصل بازرسی را به گونه یی تعیین کرد که متوسط مجموع هزینه های تعویض و بازرسی کمینه شود.
کلیدواژگان: نگه داری و تعمیرات بر اساس شرایط، مدل تلفیقی نرخ خرابی، هزینه های بازرسی، بهترین فاصله ی زمانی بین بازرسی ها، ماتریس احتمال انتقال وضعیت -
صفحه 113در این نوشتار الگوریتمی ترکیبی بر مبنای روش «بهینه سازی گروه ذره ها» برای حل مدل توسعه یافته ی میانگینواریانس انتخاب سبد سهام ارائه می شود. اغلب، برای تطابق مدل اولیه میانگینواریانس با دنیای واقعی، محدودیت های مختلفی به آن افزوده می شود. در این نوشتار، چهار نوع محدودیت، محدودیت کاردینالیتی)شامل محدودیت روی نسبت هر سهم در سبد و تعداد)نوع(سهم در سبد(، حداقل مقدار معامله و ارزش بخش لحاظ می شوند. با استفاده از سه گروه از داده های نمونه، نتایج اجرای الگوریتم جدید موسوم به C B I P S O)ترکیب بهینه سازی گروه ذره های ارتقاء یافته و دودویی(و یک الگوریتم ژنتیک، براساس چهار معیار، مورد مقایسه قرار می گیرند. معیارهای مورد ارزیابی عبارت اند از سرعت رسیدن به جواب، میانگین جواب های به دست آمده، بهترین جواب حاصل در چند اجرای متوالی الگوریتم و انحراف معیار جواب ها. همچنین تحلیل حساسیت عملکرد C B I P S O با تغییر پارامترهای مختلف در الگوریتم و مسئله بررسی می شود. نتایج تحقیق نشان می دهند که C B I P S O به طور کلی، و به ویژه وقتی که تعداد سهم های در دسترس و یا تعداد سهم در سبد زیاد می شود، بهتر از الگوریتم ژنتیک، عمل می کند.
کلیدواژگان: انتخاب سبد سهام، حداقل مقدار معامله، محدودیت های کارینالیتی، ارزش بخش، بهینه سازی گروه ذره ها -
صفحه 127در این نوشتار مدلی دوسطحی با یک تامین کننده و یک خرده فروش در حالتی که در فرایند تامین عدم قطعیت وجود دارد توسعه داده خواهد شد. در این زنجیره ی تامین، تامین کننده و خرده فروش برای کنترل سیستم موجودی خود از سیاست «مرور دائم» استفاده می کنند. تامین کننده، برای تامین اقلام خرده فروش، به صورت تصادفی در دسترس خواهد بود. در این مدل، خرده فروش با یک تقاضای پواسون مواجه است. همچنین زمان های حمل ونقل ثابت فرض شده اند. در این زنجیره ی تامین یک پارچه، مدت تحویل از جمع زمان حمل ونقل)که مقداری ثابت است(و تاخیر تصادفی یی که به علت نبود کالا در تامین کننده ممکن است رخ دهد به دست می آید. بنابراین، مدت تحویل یک متغیر تصادفی غیرمنفی است. برای اولین بار در ادبیات موضوع، در این نوشتار دو عامل «یکپارچگی» و «عدم قطعیت» در تامین را به صورت همزمان در مدل سازی مسئله لحاظ می شود. با استفاده از ایده ی سیستم موجودی پایه، یک برآورد مناسب برای سیستم تشریح شده ارائه می شود. در انتها، با استفاده از شبیه سازی نشان داده می شود که برآورد ارائه شده با خطای بسیار ناچیزی عمل می کند.
کلیدواژگان: زنجیره ی تامین، سیستم موجودی مرور دائم، مدت تحویل غیر صفر، تقاضای پواسون، عدم قطعیت در تامین - یادداشت فنی
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صفحه 133با توجه به نقش حساس مجموعه اکسل، بالاخص کاسه چرخ خودرو، به دلیل مرتبط بودن آن با ایمنی سرنشینان، بررسی فرایند تولید و مونتاژ و نیز انجام آزمایش های کنترل کیفی حین این مراحل از اهمیت به سزایی برخوردار است. در این نوشتار با توجه به اهمیت بالای سه عامل اصلی قطر توپی قسمت کاسه نمد، قطر داخلی کاسه نمد و گشتاور مهره قفلی به عنوان متغیرهای مستقل، می کوشیم میزان گشتاور چرخشی کاسه چرخ خودرو را)تحت عنوان متغیر پاسخ اول(، به کمک مباحث مطرح در طراحی آزمایش ها و روش شناسی رویه ی پاسخ و لقی کاسه چرخ) تحت عنوان متغیر پاسخ دوم (به کمک روش رگرسیون فازی با کاربرد برآوردکننده های کم ترین انحراف مطلق بهینه کنیم. در نهایت جواب بهینه با استفاده از روش L P سنجی بررسی شده است.
کلیدواژگان: طراحی آزمایش ها، رگرسیون فازی، روش شناسی رویه پاسخ، کنترل کیفیت، کاسه چرخ، مجموعه اکسل، متغیر پاسخ
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Page 3Within the context of the knowledge-based economy, individuals increasingly control their own development, careers and destinies, rather than the organisations that employ them. The term; ``human capital'' refers to the productive resources of employees that create value for themselves and for the organisations of which they are a part (Gratton & Ghoshal, 2003).The organisational perspective refers to human capital as `the source of innovation and strategic renewal' (Bontis, 1998). On an individual level, human capital is defined as a combination of four elements; genetic inheritance, education, experience, and attitudes about life and business (Hudson, 1993). The development of human capital is dependent on an individual's ability to identify and manage learning needs; learning and optimising the use of learning through career planning, job search skills and managing a work/life balance. Social capital refers to the networks of relationships that provide access to the resources that the members of the network possess or have access to. So, social capital is fluid, and reciprocal relationships with people help individuals to develop intellectual capital by accessing the knowledge and skills those people possess.Career success is commonly defined as the positive psychological or work-related outcomes or achievements one accumulates as a result of work experience (Judge et al., 1995). From this definition, career success can be viewed from both objective and subjective perspectives (Van Maanen & Schein, 1977). Hall & Chandler (2005) asserted that the subjective career is most pertinent from the vantage point of the individual, as he evaluates different facets of his career. In this subjective attitude, career success is in the eye of the beholder and reflects the importance of a person's own set of values, attitudes and goals in judging his or her career success. In contrast, Hughes highlighted the criticality of the objective career when considering the antage point of society, and an external perspective that `validate's the tangible facets of an individual's career, such as income, promotions, hierarchical job levels and job mobility (Hughes, 1958; Van Maanen & Schein, 1977; Hall & Chandler, 2005). Exploration of the subjective career is, and continues to be, timely, given the fundamental shift that has occurred within the career context (Hall & Mirvis, 1995; Arthur & Rousseau, 1996).Current literature suggests that researchers study both subjective and objective career successes for credibility. Thus, in this paper, we examine subjective and objective career success.Since most studies, up to now, have focused on the organizational outcome of human and social capital, this study was to investigate the relationship between human and social capital, and job success. Towards this goal, this study is of applied research and, based on the type of data gathering, is descriptive/correlational. In doing so, we use hierarchical regression analysis (step-by-step), in order to test the hypotheses. Demographical variables, such as; ``sex'', ``job experience'', ``age'' and ``educational status'', are regarded as control variables. Then, the effect of independent variables on dependent variables was measured. The study sample consists of 219 branch managers of Mellat Bank.The results suggest that, according to hierarchical regression analysis, human and social capital have a positive effect on objective and subjective job success. Human capital only has an effect on objective career success, but, social capital has a significant effect on both objective and subjective career successes. This implies that in the case of the subjects studied, the human capital dimension, which includes technical knowledge and skills learning capacity, has a significant effect on creating and increasing objective and subjective job successes. The social capital dimension includes relationships with key persons in the organizational network, and reliability, which have the most effect on objective and subjective job success or, more precisely, internal job satisfaction.The surprising point is that the effect of social capital was much greater than the effect of human capital on objective job success.Keywords: human capital, social capital, perceived organizational support, career success
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Page 11The hub location problem is widely used in the real world for areas, such as communications, postal services, transportation, and airline systems. This problem is applied to a network with high flow between nodes. The goal of the hub-location problem is locating some hub facilities on the nodes, and allocation of other nodes to hub facilities, in order to minimize the total cost of service. The hub facilities may face a queue of service from demand nodes, due to limited service capacity, and, hence, considering the queue in the model, may improve the performance of the system.We consider the waiting time to receive the service, as well as the total cost of networks, as the objectives of the problem, and formulate a multi objective mathematical model under a fuzzy environment. We assume the flow rates between nodes and service rates at hub facilities are fuzzy numbers. We use the credibility theory in modeling the problem, which is a new approach in formulating optimization problems in a fuzzy environment. To the best of our knowledge, this is the first attempt to formulate a hub location problem considering multi objectives using the credibility theory.The decision variables in the problem are the location of hub facilities on the network, as well as allocation of demand nodes to hubs. The objective function is to minimize the total waiting time in hubs and to minimize the expected cost in hubs to serve the demand nodes. The constraints of the model are general constraints that are assumed in hub location problems. We assume that the service demand flows from nodes to hubs, and the service rate in hubs, are fuzzy umbers.Therefore the waiting times in hubs are formulated in a fuzzy manner and we use the credibility theory to formulate and solve the problem.To solve the problems in the credibility environment, we need to use the fuzzy simulation approach. Therefore, we propose a hybrid intelligent solution method, integrating fuzzy simulation and the simulated annealing method. A DOE approach is applied to tune the parameters of the solution method and, hence, the performance of the solution method is improved. The computational results show the reasonable performance of the solution method.Keywords: hub location problem, queuing theory, fuzzy programming, fuzzy simulation, hybrid intelligent algorithm, simulated annealing
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Page 21In almost all societies, information technologies have caused the accumulation and interaction of knowledge to be increasingly reshaped, with significant ramifications affecting the processes of acquisition and dissemination of knowledge. Accordingly, universities and other educational institutions, as the main agents of the production and communication of science, will need to be gradually modified or readjusted. Hence, establishing virtual niversities, aimed at the realization of e-learning, is a challenging issue, upon which higher education managers and uthorities should concentrate more seriously. To attain this objective, certain preparatory aspects need to be materialized in various areas as a necessary precondition; systemically referred to as ``e-learning readiness'' or simply as``e-readiness''. Assessing the capabilities of the educational system for the uccessful ntroduction and mplementation of e-learning programs is of paramount importance towards achieving the goals of national higher education.To serve the above purpose, this survey attempts to propose a proper framework for strengthening existing capabilities and identifying possible deficits. As such, the first part of the paper elaborates on an appropriate model developed for assessing the e-learning readiness of Iranian higher education institutions, based on comparative studies, as well as national expert views. The designed model encompasses fourteen main aspects for assessing the status of each university against the background of a virtual education environment.This aspect includes: educational policies, administration, standards, content, rules and regulations, financial resources, human resources, culture, security, hardwareequipment, communication network, logistics, supervision and coordination. It is noteworthy that the proposed model has been objectively tailored, in accordance with the particular features and local characteristics of the country, and has eventually been applied and tested against a real ituation in one of the most prestigious national universities for complementary studies. Thus, it is assumed to be flexibly adaptable and safely advisable to be practically applied for assessing e-learning readiness in all universities country wide.Keywords: e, learning, virtual university, e, readiness, assessment, tarbiat modares university
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Page 31A pre-requisite for predicting the performance of any process is nothing but a study of the factors affecting the process and their interactions. Conventional methods, like the design of experiments, as well as unconventional methods, like artificial neural networks (ANN), are two major approaches for the discovery of such interrelations. Each of these approaches enjoys its own unique advantages in modeling a production process. A conventional method defines the variables based on, for example, statistical analysis, and, on the basis of the outcome, practitioners are well positioned to form their interpretations and draw their inferences about rocess erformance. Unconventional methods, in turn, have their own advantages. ANNs, for instance, have such advantages as; simplicity of application, high degree of reliability in discovering complicated interactions among variables, and last, but not least, being inexpensive as a practical method.There are reports in the literature which are devoted to comparison of the performance of unconventional models against conventional ones. This paper is dedicated to such a cause, in the sense that it attempts to model the complicated spray drying process by the logistic regression approach (a conventional method), as well as ANN's (an unconventional method), in order to compare the performance of these methods in predicting (by interpolation and extrapolation) process performance.Once the conceptual model of the spray drying process is developed, the model building process for the logistic and ANN is described through the following steps: a) designing the model architecture; b) data collection and processing; c) defining the model structure; d) selecting the right criteria for fitting the model; e) estimating the parameters of the model; f) verifying the model; g) selecting the right criteria for model reliability; and h) evaluating model reliability. The logistic and ANN models are fitted by a set of 100 data values, and are, subsequently, tested and evaluated by another set of 30 data values.Based on the results, in terms of the coefficient of determination and the percentage of correct predictions, it can be concluded that the ANN model demonstrates a relative edge over the logistic model in predicting process performance. It is obvious that there is room for sharpening this edge by increasing the number of test data. By establishing the superiority of one method over another in predicting process performance, one may define and investigate various scenarios, in order to arrive at conditions under which the input variables are so tuned that the quality of predicting the process performance is desirably enhanced.Keywords: performance prediction, artificial neural networks, modeling, logistic, regression, spray drying
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Page 39This study is an applied research into evaluation of the competency of equipment manufacturers in the oil ndustry. Nowadays, by considering the complexity of global competition, gradually, traditional evaluation has been replaced by scientific and expert processes. The importance of the oil industry in Iran, and the above mentioned factors, require that special attention should be paid to evaluate all equipment manufacturers. In this paper, we recognize nine attributes for evaluation of equipment manufacturers. Then, we assign four categories of the firms, namely; outstanding, good, moderate and weak, using the PROMSORT technique.PROMSORT is ROMETHEE-based MCS method that assigns alternatives to predefined ordered categories. The assignment of an alternative (for example, a) to a ertain ategory s erformed using both profiles; defining the limits of the categories and the reference alternatives in different steps.After an assignment of alternatives, based on the limits of categories, it is possible that some alternatives could not have been assigned to a category, since outranking relations indicate that these alternatives are indifferent or incomparable to a limited profile and cannot be assigned to a category directly. On the other hand, some alternatives could be assigned to the categories. At this stage, we will use these alternatives as the reference actions of the categories, to be able to assign the alternatives that have not yet been assigned.looseness=-1In our methodology, we wish for all our companies to achieve better scores, in order to assign them an upper category. We suggest plans for improving the performance of these criteria. In order to identify the differences among company groups, we used a single criterion net flow.In the last stage, we use figures for illustrating the position of companies. In order to compare the companies, we determine the average, single criterion net flow for each group, and, in the same manner, each company can be compared with limited profiles.We propose a company evaluation and management methodology for the improvement process, in which companies are categorized and compared, according to their performances, using several criteria. Performances of the companies are improved by applying company improvement programs.In this study, we compared five companies and suggested programs for improving their performance. We can use this method for more companies, and with more attributes, in other industries.Keywords: PROMETHEE, PROMSORT, evaluation, industrial manufacturer
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Page 47In this article, a multiproduct production-inventory system with stochastic demand and production time, with and without capacity constraint, is considered. Our purpose is to determine the optimal conditions for each product when we must select between make to stock and make to order production systems. The objective is minimizing total inventory and backlog costs. We include the new assumptions regarding the models found in the literature by considering imperfect quality and delayed inspection. Also, the results of a single stage are extended to a multi stage production system, where there is a network of machines. The problems are modeled using queue theory principals.Consider a manufacturer that produces different items with stochastic demand. The processing times of an item at each stage of the production process are random variables. If there are a great number of parallel processors at each stage, then, an infinite capacity for the manufacturing system is assumed.In this paper, first, we considered a single stage production system with infinite capacity. There is a given probability to produce a defective item. The detected defective items are not recycled into the system and are waste items. The inspection time is very short, compared with processing time, and is ignorable. The processing times and demands follow the Poisson probability distribution.The second developed model is similar to the first, but, with one difference. Here we limited the capacity of the production.The third model is an extension of the second one, where we consider a non-zero inspection time of the final product. The results show that inspection time has no influence on the optimal policy.%looseness=1Finally, we developed multi stage models in two cases: infinite and finite capacity. In multi stage systems, there is a probability for a given item to ontinue the process from one stage to the next. Also, the number of necessary stages to complete an item is a random variable, and, at each stage, there is a probability that an item will go directly to the inventory store.looseness=-1Consideration of machine breakdown probability and limited storage capacity could be suitable topics for further research.Keywords: inventory, production system, make to order, make to stock, queuing theory, inventory cost, shortage cost
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Page 55Over the last decade, the project management office (PMO) has become a prominent featurein any rganizations. According to the project management literature, the PMO can be defined as an organizational body or entity that is assigned various responsibilities relating to the centralized and coordinated management of those projects under its domain. The PMO responsibilities can range from providing project management functions to directly and actually being involved in the management of the projects. Despite the proliferation of PMOs, in practice, our understanding of this phenomenon remains sketchy at best. No consensus exists as to the way PMOs are, or should be, structured, neither the functions they should undertake in organizations. Considering this fact, the aim of this study is to investigate the reality of PMOs in the oil, gas, and petrochemical industry of Iran. This study is the first empirical study in Iran, so, it can be used as a landmark for other organizations to decide what they expect from a PMO.Due to lack of sufficient empirical research on the subject of PMOs, a reliable portrait of PMOs is not available. So, this research tries to provide such a portrait. This includes many aspects, such as the reasons for establishment of PMOs and their challenges, PMO functions, the number of projects under their control, the degree of their authority and the age of PMOs. As providing a descriptive portrait is, typically, an objective of exploratory research into a previously unexplored topic, the present research should be considered as descriptive and exploratory. In this regard, nine major Iranian oil, gas and petrochemical organizations, including the participation of three qualified experts from each organization, have been studied. Therefore, a uestionnaire was developed and tested. Moreover, feedback sessions were held with informants from the organizations to validate and discuss the results.According to the research findings, the PMO is almost a new concept in this industry; nearly 60% of the PMOs have been developed during the last 3 years. The term `projectmanagement offices'' is used in the majority of studied organizations with a variety of roles and functions. Monitoring project performance, providing project software and tools, and preparing project management methodologies are the most applied functions. These functions aim to support the golden triangle (cost/time/ quality) of project objectives. Moreover, the most significant challenges for PMOs are the risk of changing organizational culture and the lack of professional staff. It is suggested that this research is developed by an investigation into the concept in other industries.Keywords: project management office (PMO), project management, engineering, procurement and construction (EPC), organizational project management maturity model (OPM3)
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Page 65With the daily increase in competition and the focus of organizations on developing their strategic management, the definition and implementation of efficient performance evaluation methods are recognized as powerful tools for improving competitive advantage. One of the most popular methods for performance evaluation is the "Balanced Scorecard". A feature in the implementation of the "Balanced Scorecard" that has attracted researchers in the past few years is the ranking of the key performance indicators (KPI).In this article, a strategy focused model is presented, which uses a combination of the ``Balanced Scorecard'' and the ``Fuzzy Analytic Network Process'', in order to make a ranking of KPIs. The results of its implementation in the Isfahan municipality dependent organization (the Mayadin organization) are also mentioned.Keywords: strategic management systems, balanced scorecard, weighting and ranking, analytic hierarchy process, analytic network process, fuzzy
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Page 75Group scheduling within the context of sequence dependent setup times in a flexible flow shop, with minimizing the makespan as the objective (FFm$|$fmls, S$_{plr}$$|$C$_{max}$), is considered in this research. A mixed integer linear programming model is developed for the research problem. Since the proposed research problem is proved to be NP-hard, two different metaheuristic approaches, based on simulated annealing (SA), are eveloped to solve the problem heuristically. The search space of the algorithm is increased by permitting the searching process to repeat at each temperature, N times, where N is the length epoch. Several stopping criteria are used to increase the searching speed of the proposed SA-based heuristic. Intense mutation is also applied to prevent the search becoming trapped in local optimum. In intense mutation, the positions of two random groups at each stage are exchanged. Since generating the initial solution in the area of a flexible flow shop has its own omplexities, four different initial solution (IS) finding mechanisms, with varying levels of computational difficulty, are also developed to aid the search algorithms in identifying an IS.In this research, we use two approaches to generate initial and neighboring schedules. In the first approach, the sequence of groups and jobs at the first stage are determined, to show an initial solution. The job sequences from stage two to the last stage are determined according to the FIFO rule, so that groups are ordered according to their first job completion time at the previous stage. In other words, a group whose first job is completed sooner at one stage will be processed sooner at the next stage. Allocation of groups to identical parallel machines is determined according to a greedy algorithm. Based on this algorithm, the group is assigned to a machine at each stage when the process of jobs of the group is completed sooner than other machines at the stage. In the second approach, to show an initial solution, the assigned groups to each machine at each stage, and the sequence of groups and jobs on each machine at the first stage, are determined. Then, the sequence of groups, as well as the jobs belonging to that group at other stages, is determined, according to the FIFO rule. The assignment of groups to the parallel machines of a stage, in stages two to m, is determined, according to the greedy algorithm. In order to find the best neighboring solution, a two-level, SA based metaheuristic algorithm is proposed. At the first level, the neighborhood for the group sequence is obtained by performing an outside perturbation on the group sequence. Outside perturbation on the group sequence is performed by three neighborhood mechanisms, namely: the shift move (SM), the pairwise interchange (PI) and transfer to another machine (TAM). At the second level, the neighborhood for the job sequence is obtained by performing the inside perturbation on the job sequence. For inside perturbation, the partial pairwise interchange mechanism is used.%looseness=1 For evaluating the performance of the proposed algorithms, the makespan value and the elapsed time to solve the test problems are considered as two response variables; representing the effectiveness and efficiency of the algorithms. Based on obtained results using makespan, the proposed SA algorithm, in which the sequence of groups and jobs at the first stage provides the initial solution, with an initial solution random generating mechanism, is recommended for all sizes. For the elapsed time, the SA algorithm, in which the sequence of groups and jobs at the first stage is used as an initial solution with an initial solution random generating mechanism, provides a better result than the other proposed algorithms. The performance of the metaheuristic algorithm is compared with the only available metaheuristic algorithm in literature, i.e., the Tabu search, to evaluate the quality of the proposed algorithm. The results show that the proposed SA algorithm in this research has a superior performance to the Tabu search, based on a paired t-test comparison.Keywords: sequence, dependent group scheduling, flexible flow shop scheduling, metaheuristics, simulated annealing (SA), mathematical programming, minimization of makespan
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Page 93In this paper, we introduce two robust models to create a portfolio with the best combination of risk free asset, stocks and options within multi-periods.Many input parameters of model, such as stocks or options price, are uncertain. If they are estimated as deterministic values, portfolio optimization may result in infeasible solution. Among different approaches for handling uncertainties, we adopt robust optimization.First, as a basic model, we formulate the problem with deterministic data. The decision variables are the amount invested in the free risk asset, the number of stocks as well as the number of options (both call and put) to include in the desired portfolio. The objective is to determine the optimal combination of assets in order to maximize the total return at the end of last period. The constraints represent the limitation on initial investment budget in the first period; the available budget at the end of each period which includes new investment opportunity for next period plus the return of existing investment and finally the constraint that calculates final return of portfolio. No shortselling is allowed.For developing the robust model, uncertainty of stock prices at the end of each investment period are presented within linear intervals.In the first model, we develop a robust counterpart which results in the best solution, if the worst situation within the intervals occurs. It is a conservative counterpart robust model in which the relations between the uncertain parameters, such as the value stocks and options, is nonlinear (linear piecewise).In the second model, each constraint has a special set of uncertain parameters which works independently from the other constraints. Therefore, for controlling the feasibility of solution, each one must be considered separately. This model is a robust counterpart of for multi-period and option based portfolio optimization problems. Optimal solution of this model is feasible for each combination of stock value for future periods. The optimal solution shows the best solution of the model for the worst combination of sock value for future periods. However, we consider an upper limit for protection level of uncertainties of all constraints. In fact, for dealing with this problem and improving our model, we introduce a controlling factor for investor risk acceptance in investment. It is clear the chance of realization of the worst case stock value combination at each period is very low.In the second model, we adopt a different approach to develop a counterpart model which is controllable, as far as its conservative degree is concerned. To handle uncertain nonlinear parameters, we introduce a new approach to develop the proposed modes.To solve the models, they are reformulated as dual problems. In this way, the optimal solution can be obtained analytically.To analyze the models, we solve three problems with 100 stocks and 400 options and study the results.Keywords: portfolio optimization, options, robust optimization
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Page 103Condition-based maintenance (CBM) is a maintenance strategy that recommends maintenance actions based on information collected through condition monitoring (periodic inspections). The primary goal of CBM is to extend the lifetime of systems, to avoid unnecessary preventive maintenance, and to improve equipment reliability.There has been much research, attempting to include economic considerations, into the process of decision making in CBM. A well-known approach is called the; control limit policy. In this approach, it is assumed that the inspections are performed at fixed and given intervals of times. The equipment is replaced whenever it fails. Also, after each inspection, and based on inspection results, if the cost-related failure rate reaches or exceeds a pre-determined limit, a preventive replacement is scheduled. The limit is determined, such that the expected average aintenance costs per unit time, due to preventive and failure replacements over a long time horizon, are minimized.Clearly, a higher frequency of inspection may provide more information about the condition of the equipment and, thus, maintenance actions are performed more effectively. Consequently, the cost associated with failure and preventive replacements is decreased. But, in many real cases, inspection requires labour, specific test devices and, sometimes, suspension of operations. Thus, when the inspection and analysis of observations are costly, performing inspections at short intervals incur large inspection costs. In contrast, if inspections are carried out over long intervals, the cost of failure replacements may significantly increase. Therefore, it is necessary to consider not only the preventive and failure replacement costs, but also inspection costs in CBM. This paper extends the control limit policy to include inspection costs for optimization of inspection intervals and control limits, simultaneously. For different alternative inspection intervals, the optimal control limit is determined and, then, the associated costs are compared to identify the optimal inspection interval and the optimal control limit. A numerical example is given to illustrate the proposed approach.Keywords: condition, based maintenance, proportional hazard model, inspection costs, optimal inspection interval, transition probability matrix
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Page 113The selection of an appropriate portfolio of assets to invest is the major concern for fund management companies as well as individual investors. The attractiveness of a security to an investor is not only based on its arithmetic mean of return, but the standard deviation of the asset's return and its correlation with other securitie's return in the portfolio play an important role in the selection process as well. Having defined risk as the standard deviation of the portfolio's return, the decision to be made is to select a subset of assets (with their corresponding weights) out of a given set of assets in such a way that the constructed portfolio yields the minimum amount of risk for a given level of return. The solution for this problem, also known as the standard Markowitz portfolio selection problem, can be determined using his proposed Critical Line method. However, the computational complexity increases when the total number of available assets is high and/or other realistic constraints are included into the problem.This paper presents a novel heuristic method for solving an extended Markowitz mean-variance portfolio selection model. The extended model includes four sets of constraints: bounds-on-holdings, cardinality, minimum transaction lots, and sector (or market/class) capitalization constraints. The generalized model is classified as a quadratic mixed-integer programming model necessitating the use of efficient heuristics to find the solution. Some heuristic methods based on Genetic Algorithm, Simulated Annealing, Tabu Search and Neural Networks have been reported in the literatures. In this paper, we propose a novel heuristic based on Particle Swarm Optimization method. The approach is based on two parts integrated to each other: one that selects M securities out of N available securities (satisfying the cardinality constraints) and the other part that seeks best positive integer investment weights, for the M selected securities.The proposed approach is illustrated and compared with Genetic Algorithm subject to four performance criteria commonly used in literature. The criteria are the best variance among the risks obtained from the algorithm runs, the mean portfolio variance found, the standard deviation of obtained variances, and the mean run time. The computational results show that the proposed approach outperforms Genetic Algorithm and can effectively solve large-scale problems.Keywords: portfolio selection, minimum transaction lots, cardinality constraints, sector capitalization, particle swarm optimization
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Page 127In this paper, we consider a dyadic supply chain with an uncertain supplier. Most existing studies in supply chain and inventory literature assume that the supplier is continuously available to get the order from the retailer. In this study, this assumption is relaxed and we assume that the supply process is unreliable. An unreliable supplier alternates between available (ON) and unavailable (OFF) states. The ON and OFF durations are considered to be independent exponential variables. Both the retailer and the supplier use a (R, Q)-type continuous review policy. The retailer faces Poisson demands. The transportation time between the outside supplier and the supplier, as well as the transportation time between suppliers and the retailer, are assumed to be constant. The lead time that the retailer experiences is a non-zero random variable, which is composed of constant transportation time and a random delay that occurs due to lack of inventory at the supplier. The shortage at the retailer is backordered, and delayed retail orders are satisfied on a first-come, first-served base. The main contribution of this paper is considering both the integrity and uncertainty in the above supply chain. Using the idea of the one-for-one ordering policy cost, we derive a reliable approximation for the total cost function of the described system, as a weighted mean of costs of a one-for-one ordering policy. Finally, using simulation studies, we show that absolute errors are ignorable.Keywords: continuous review, non, zero random lead time, poisson demand, supply chain management, supply uncertainty
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Page 133Considering the crucial function of the axle assy, especially the vehicle brake drum, due to its relevance to the safety of the passengers, studying the production and assembly processes and conducting quality control experiments during these stages is of great importance.In this study, two approaches are used to improve the vehicle brake drum assembling process. The first approach is named; response surface methodology (RSM). Response surface methodology is the most popular optimization method used in recent years. There is so much work, based on the application of RSM in chemical and biochemical process. The effects of process parameters for the vehicle brake drum assembling process were exploited using the; design of experiment (DOE). In this work, experiments are performed by a standard RSM design, called a central composite design (CCD). With regard to the great significance of three main factors, namely; seal-oil spindle diameter, seal-oil internal diameter, and nut lock torque, as independent variables, the present research attempts to optimize the rotatory torque of the automobile brake drum (as the first response variable) obtaining assistance from discussions regarding the design of experiments and the response surface methodology. The second approach is named; fuzzy regression. There is a likelihood that the greater the values of independent variables, the wider the width of the estimated dependent variables. This causes a decrease in the accuracy of the fuzzy regression model constructed by the least squares method. In this paper, we use the least absolute deviation estimators to construct the fuzzy regression model, and investigate the performance of the fuzzy regression models, with respect to a certain error measure. Simulation studies and examples show that this model produces less error than the fuzzy regression models studied by many authors, which use the least squares method when the data contains fuzzy outliers. Also this article attempts to optimize the unsteady of the automobile brake drum (as the second response variable) getting help from fuzzy regression using least absolute deviation estimators (FLAD).In the following parts, the amount of optimum effective factor has been calculated via the nonlinear programming model, using one of the multi-objective methods (LP - Metric).Keywords: design of experiment, fuzzy regression, response surface methodology, quality control, brake drum, axle assy, response variable
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