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جستجوی مقالات مرتبط با کلیدواژه

multi-objective programming

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تکرار جستجوی کلیدواژه multi-objective programming در نشریات گروه فنی و مهندسی
تکرار جستجوی کلیدواژه multi-objective programming در مقالات مجلات علمی
  • Pouria Hajiamoosha, Abdollah Rastgou *, Hadi Afshar
    In this paper, a multi-carrier energy hub that can generate and deliver electricity, heating, and cooling ‎energy from different sources, such as wind, solar, fuel cells, batteries, and compressed air is ‎proposed. The intelligent energy hub can also participate in electrical and thermal demand response, ‎which aims to reduce peak demand and enhance overall system efficiency. The scheduling problem is ‎a mixed-integer linear programming problem that seeks to minimize the system cost and carbon ‎dioxide emissions. To obtain optimal solutions that strike a balance between cost, emissions, and ‎decision maker's preferences, an augmented epsilon-constraint min-max fuzzy method is employed. ‎The proposed strategy's advantages are demonstrated through a case study, where it is compared with ‎other methods. The results show that the proposed approach effectively reduces the cost and ‎emissions of the smart energy hub while improving the load shape and energy hub efficiency. ‎Moreover, the results showed that the integration of compressed air systems and demand response ‎programs enhances the performance of the smart energy hub, making it more flexible and reliable. ‎The GAMS software is employed for the modeling and resolution of the scheduling issue.‎
    Keywords: Energy Hub, Multi-Objective Programming, Storage Devices, Optimization
  • سیما غایب لو*، فریبا فتحی پور، مهسا علیمحمدی
    تولید کمپوست از مواد زاید دارای سابقه طولانی می باشد و از دیر باز از روش های متفاوتی برای تولید کمپوست استفاده شده است. علیرغم اهمیت بالای کمپوست به عنوان کود ارگانیک برای باروری محصولات کشاورزی، مرور ادبیات زنجیره تامین تولید کمپوست نشان می دهد که این مساله چندان مورد توجه قرار نگرفته است. از طرف دیگر،کیفیت کمپوست تولید شده بسیار حایز اهمیت می باشد. در این مقاله با یک نگاه نوآورانه در قالب روش تحلیل سلسله مراتبی به آن پرداخته شده است. از این رو مقاله حاضر با ارایه یک مدل چند هدفه به چگونگی فرآیند تولید کمپوست و طراحی زنجیره تامین آن و بررسی کیفیت کمپوست، هزینه های کمپوست و همچنین کاهش آلایندگی زیست محیطی گازهای گلخانه ای حاصل از آن پرداخته است. برای حل مدل چند هدفه از روش های مجموع وزن دهی شده و اپسیلون محدودیت استفاده شده است. مدل برای یک مطالعه موردی حل و کارایی مدل ارایه شده بررسی و با توجه به تحلیل حساسیت های انجام گرفته، بینش های مفید مدیریتی در ارتباط با تعیین ظرفیت بهینه تامین کنندگان و تولید کنندگان، بهبود کارایی زنجیره تامین کمپوست با در نظر گرفتن تابع هدف کیفیت کمپوست، تعیین وسیله حمل و نقل مناسب با در نظر گرفتن اولویت های مدیریتی در مورد هزینه کل زنجیره تامین و الزامات قانونی مربوط به انتشار آلاینده ها و تعیین روش تولید بهینه کمپوست استخراج شده است.
    کلید واژگان: طراحی زنجیره تامین کمپوست، برنامه ریزی چند هدفه، کیفیت کمپوست، مجموع وزن دهی شده، اپسیلون محدودیت
    Sima Ghayebloo *, Fariba Fathipour, Mahsa Alimohammadi
    For a long time, waste materials have been used to produce compost by different methods. Despite the high importance of compost as an organic fertilizer for the fertility of agricultural products, the literature review on the compost supply chain shows that this issue has not received much attention. On the other hand, the quality of the compost produced is very important, which is considered by an innovative glance in the form of analytical hierarchical analysis method, in this paper. Therefore, a multi-objective model proposed which discusses the compost production process, compost supply chain design, compost quality, compost supply chain costs and furthermore the reduction of greenhouse gases emission. The multi-objective model is solved by weighted sum and epsilon constraint methods. The model is implemented for a case study to discover the efficiency of the proposed model. According to the sensitivity analyses, useful managerial insights regarded to determining the optimal capacity of suppliers and producers, improving the efficiency of the compost supply chain by considering the quality objective function, determining the appropriate transportation equipment taking into account the management priorities based on the entire supply chain cost and the legal requirements based on the emission of pollutants and determining the optimal method of compost production are extracted.
    Keywords: compost supply chain design, Multi objective programming, compost quality, Weighted Sum, Epsilon constraint
  • Ali Namazian *, Siamak Haji Yakhchali, Masoud Rabbani
    This paper presents a novel formulation of the integrated bi-objective problem of project selection and scheduling. The first objective is to minimize the aggregated risk by evaluating the expected value of schedule delay and the second objective is to maximize the achieved benefit. To evaluate the expected aggregated impacts of risks, an objective function based on the Bayesian Networks is proposed. In the extant mathematical models of the joint problem of project selection and scheduling, projects are selected and scheduled without considering the risk network of the projects indicating the individual and interaction effects of risks impressing the duration of the activities. To solve the model, two solution approaches have been developed, one exact and one metaheuristic approach. Goal Programming method is used to optimally select and schedule projects. Since the problem is NP hard, an algorithm, named GPGA, which combines Goal Programming method and Genetic Algorithm is proposed. Finally, the efficiency of the proposed algorithm is assessed not only based on small size instances but also by generating and testing representative datasets of larger instances. The results of the computational experiments indicate that it has acceptable performance to handle large size and more realistic problems.
    Keywords: Project selection, scheduling, Risk analysis, Bayesian Networks, multi-objective programming, Genetic Algorithm
  • Masood Rabieh *, Leila Babaee, Abbass Fadaei Rafsanjani, Mehdi Esmaeili
    The purpose of the current study is to select suppliers and determine their order allocation in a way that the performance of the sustainability of the supply process gets optimized on the whole. In this research, after reviewing the literature and investigating the supply chain of the case study (Iran Khodro’s supply chain) through Delphi method, a set of evaluation criteria related to the performance of the suppliers in economical, social and environmental terms was identified. In the next stage, by using the identified criteria, the multi-objective mathematical integer programming was presented to solve the problems of suppliers’ selection and order allocation. The suggested mathematical programming in this research is designed to be multi-product, single-period and multiple sourcing. Fuzzy TOPSIS method is applied to calculate the qualitative parameters that are used in the suggested mathematical programming. Ultimately, the mathematical model suggested in the research will be solved by two methods, i.e. Epsilon Constraint Method and Weighted Sum Method. Moreover, the total value of the sustainable purchasing (TVSP) will be calculated for both cases. Comparing these two methods indicates that in this research the results of weighted sum method are better than those epsilon constraint method.
    Keywords: Sustainable Supplier Selection, Order allocation, Fuzzy TOPSIS, multi-objective programming, Epsilon Constraint Method, Weighted Sum Method
  • D. Veysmoradi, B. Vahdani *, M. Farhadi Sartangi, S.M. Mousavi
    In this study, the response phase of the management of natural disasters is investigated. One of the important issues in this phase is determining the distribution areas and timely distribution of relief to affected areas in which transportation routing is of a critical matter. In the event of disasters, especially flood and earthquake, terrestrial transportation is not that much easy due to the damage to many infrastructures. For this reason, we propose that delivering relief from the distribution areas to disaster stricken places should be done simultaneously by terrestrial as well as aerial transportation modes to increase route reliability and reduce travel time. In this study, for relief allocation after earthquake, we offer a mixed-integer nonlinear open location-routing model in uncertainty condition. This model includes several contradictory objectives and variety of factors such as travel time, total costs, and reliability. In order to solve this model, a hybrid solution by combining robust optimization and fuzzy multi-objective programming has been used. The performance and effectiveness of the offered model and solution approach has been investigated through a case study on the earthquake in East Azerbaijan, Iran. Our computational results show the solution we have offered for real problems has been effective.
    Keywords: Emergency logistics, Relief distribution, location, routing, Split delivery, Multi-Objective Programming, Robust Optimization
  • مهدی احمدی جیردهی، وحید سهرابی تبار، رضا همتی
    در این مقاله، بر روی برنامه ریزی بهینه ریزشبکه مبتنی بر سیستم فازی- عصبی تطبیقی که در حضور بارهای الکتریکی و گرمایی، منابع انرژی تجدیدپذیر (باد و خورشید)، CHP، منابع انرژی مرسوم (میکروتوربین و بویلر)، سیستم های ذخیره انرژی (ذخایر الکتریکی و گرمایی) و تجهیزات D-FACTS است، تمرکز خواهد شد. تجهیزات D-FACTS بر روی خط ارتباطی بین ریزشبکه و خط اصلی نصب شده تا امکان تبادل توان افزایش یابد. در برنامه ریزی مطرح شده، سرعت باد، تابش خورشید و بارها به صورت تصادفی در نظر گرفته خواهند شد. مسئله مطرح شده به صورت خطی عدد صحیح مقید مدل شده و توابع هدف آن هزینه و آلودگی خواهد بود. نتایج نهایی نشان دهنده بهبود عملکرد ریزشبکه در حضور تجهیزات D-FACTS خواهد بود به طوری که هزینه به مقدار قابل توجهی کاهش خواهد یافت. همچنین، نشان داده خواهد شد که با استفاده از سیستم فازی- عصبی تطبیقی، با خطای بسیار پایین، زمان شبیه سازی به مقدار قابل توجهی کاهش خواهد یافت که در سیستم های مدیریتی با ابعاد بزرگ می تواند بسیار کاربردی باشد. مسئله تصادفی چندهدفه مطرح شده با استفاده از روش محدودیت اپسیلون ارتقایافته حل شده و تمامی نتایج با استفاده از نرم افزار GAMS24.1.3/CPLEX12.5.1 به دست آمده است.
    کلید واژگان: تجهیزات D-FACTS، برنامه ریزی چندهدفه، ریزشبکه، سیستم فازی - عصبی تطبیقی، مدیریت تصادفی
    M. Ahmadi Jirdehi, V. Sohrabi Tabar, R. Hemmati
    This paper focus on optimal scheduling of microgrid based on adaptive neuro-fuzzy inference system including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical storage), and D-FACTS devices. D-FACTS are included in the line between main network and microgrid to achieve more power transfer to the upstream grid. In the proposed planning, wind speed, solar radiation, and loads are modeled as uncertain parameters based on the stochastic approach. Problem is expressed as a linear, mixed integer, constrained, and multi objective optimization aiming at minimizing cost and pollution at the same time. Operation improvement is illustrated in final results by considering D-FACTS as cost is decreasedto a considerable amount. Also, will be shown that simulation time will be decreased to a noticeable amount that can be applicable in large scale management systems by using adaptive neuro-fuzzy inference system.The proposed multi objective and stochastic problem is solved using augmented Epsilon-constraint method. All results and calculations are calculated using GAMS24.1.3CPLEX12.5.1.
    Keywords: D-FACTS devices, multi objective programming, Microgrid, adaptive neuro-fuzzy inference system, stochastic management
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