harmony search algorithm
در نشریات گروه عمران-
به علت وجود مشکلات در ارزیابی تغییر شکل توده سنگ های درزه دار در مقیاس آزمایشگاهی، می توان برای در نظر گرفتن اثر مقیاس و درزه ها از روش های مختلف آزمایش برجا مانند آزمایش بارگذاری صفحه ای و دیلاتومتری استفاده کرد. اگر چه این روش ها در حال حاضر بهترین هستند، اما گران، زمان بر و دارای مشکلات عملیاتی در حین اجرا هستند. بنابراین در این مقاله برای غلبه بر این مشکلات، از الگوریتم های جدید جستجوی هارمونی (HS) و الگوریتم بهینه سازی مبتنی بر آموزش و یادگیری (TLBO) برای تخمین غیرمستقیم مدول تغییرشکل پذیری توده سنگ استفاده شده است. در این مدل ها از امتیاز رده بندی توده سنگ (RMR)، مقاومت فشاری تک محوره سنگ بکر (UCS)، عمق (D) و مدول الاستیسیته سنگ بکر (Ei) به عنوان پارامترهای ورودی و از مدول تغییرشکل پذیری توده سنگ (Em) به عنوان پارامتر خروجی استفاده شده است. در این مقاله، با استفاده از شاخص های آماری مختلف، مدل ایجادشده توسط الگوریتم ها، ارزیابی و اعتبارسنجی می شود. نتایج ارزیابی نشان داد که دقت رابطه برای الگوریتم جستجوی هارمونی با استفاده از شاخص های R2 و VAF حدود 93/0-91/0 و درصد خطا با استفاده از شاخص های RMSE وMSE بین 0042/0-000017/0 است هم چنین دقت رابطه برای الگوریتم بهینه سازی مبتنی بر آموزش و یادگیری با استفاده از روش R2 و VAF حدود 95/0-92/0 و درصد خطا با استفاده از شاخص های RMSE وMSE بین 0032/0-000010/0 به دست آمد.کلید واژگان: مدول تغییرشکل پذیری، الگوریتم جستجوی هارمونی، الگوریتم بهینه سازی مبتنی بر آموزش و یادگیری، توده سنگDue to the difficulties in assessing the deformation of jointed aggregates at the laboratory scale, various in situ testing methods such as plate loading test and dilatometry can be used to consider the effect of scale and joints. Although these methods are currently the best, they are expensive, time consuming, and have operational difficulties during implementation. Therefore, in this paper, to overcome these problems, new harmony search algorithms (HS) and teaching-learning optimization algorithm (TLBO) are used to indirectly estimate the modulus of rock mass deformation. In these models, the rock mass classification score (RMR), uniaxial compressive strength of virgin rock (UCS), depth (D) and the modulus of elasticity of intact rock (Ei) as input parameters and the modulus of rock mass deformability (Em) as output parameter Used. In this paper, Using different statistical indicators, the model created by the algorithms is evaluated and validated. The evaluation results showed that the relationship accuracy for the harmonic search algorithm using R2 and VAF methods is about 0.91-0.93 and using the RMSE and MSE methods is between 0.000017-0.0042. Also, the relationship accuracy for the optimization algorithm Based on teaching and learning using R2 and VAF methods, about 0.92-0.95 and using RMSE and MSE methods were between 0.00001- 0.0032.Keywords: Deformation of modulus, harmony search algorithm, teaching-learning optimization algorithm, rock mass
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In this article, the control over the inlet sediment into the lateral intakes incorporating parallel skimming walls is assessed using harmony search algorithm. The skimming walls are known as the structures constructed in front of the lateral intake and consisted of two plates, one of them is in oblique form and the other one is parallel to the flow. The parallel skimming walls direct the sediments toward the downstream of the main channel by forming a rotational flow, as a result the entry of sediments into the lateral intake is prevented. Using the experimental data obtained in the laboratory and Buckingham’s method, the dimensionless parameters were obtained. The parameters were nonlinearly transformed into the relations, in such a way that using harmony search algorithm almost 20,000 optimal points were obtained. In the present research, the relations between the dimensionless parameters were yielded by harmony search algorithm. The results indicate that the optimized maximum and minimum and mean values of CS1 for governing equations is equal to 17%, 31% and 29%, respectively, relative to the observational maximum, minimum and mean values of CS1. For governing equation, the optimized maximum, minimum and mean values of CS2 exhibited error values of 11%, 4% and 31% relative to the observational maximum, minimum and mean value of CS2.Keywords: Lateral Intake, Skimming Wall, Sediment Control, harmony search algorithm
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سکوهای دریایی از سازه های حیاتی کشورهای نفت خیز محسوب می شوند، که معمولا تحت تاثیر بارهای دینامیکی شدید امواج دریا قرار دارند. بنابراین کنترل ارتعاش های سکوهای دریایی برای افزایش بهره وری و جلوگیری از خرابی زودرس احتمالی ناشی از خستگی، اهمیت خاصی دارد. در مطالعه ی حاضر، به ارزیابی رفتار سکوی نفتی رسالت واقع در خلیج فارس تحت ارتعاش های ناشی از دو موج با دوره های بازگشت 50 و 100 سال پرداخته شده و سپس به منظور کنترل آن از میراگرهای جرمی هماهنگ شده ی غیرفعال و فعال استفاده شده است. برای محاسبه ی نیروی کنترل از الگوریتم هوشمند فازی و برای بهینه یابی توان عملگر از الگوریتم جستجوی هارمونی استفاده شده است. همچنین اندرکنش بین سازه و سیال، جرم افزوده و اشباع عملگر در نظر گرفته شده است. نتایج به دست آمده، نشان دهنده ی عملکرد مناسب سیستم کنترلی پیشنهادی است، که مقادیر بیشینه و نرم شتاب عرشه ی سکو را به ترتیب به مقادیر 20 و 50 درصد در طول زمان کاهش داده است.
کلید واژگان: سکوی شابلونی، میراگر جرمی هماهنگ شده، الگوریتم جستجوی هارمونی، اندرکنش بین سازه و سیالIn recent decades, different control strategies (i.e., passive, active, semi-active, or hybrid) have been extensively employed to suppress the response of offshore structures subjected to dynamic lateral loads. Jacket platforms are vital structures for oil-rich countries that are frequently subjected to dynamic harsh sea waves. Therefore, the vibration control of these structures is substantial to increase productivity, safety, and serviceability and prevent premature possible fatigue failure. In this study, the behavior of the Ressalat platform located in the Persian Gulf is evaluated under wave loads with two different return periods of 50 and 100 years. A simplified equivalent seven-degree-of-freedom lumped mass linear model is adopted for the Ressalat platform. In the Persian Gulf, wave loads are the dominant load in the designing procedure. Due to the stochastic nature of wave loads, random wave and constrained new-wave theories are utilized in the generation of the wave records. Then, Passive Tuned Mass Damper (PTMD) and Active Tuned Mass Damper (ATMD) are employed to suppress the platform vibration and subsequently, their control performances are compared. Various calculated normalized performance criteria (responses of controlled to uncontrolled structures) for passive and active controlled platforms including normalized maximum and Root Mean Square (RMS) of displacement, velocity, and acceleration of the deck level are calculated and compared. The uncontrolled and controlled platforms are modeled and analyzed using MATLAB and SIMULINK software. Moreover, the fuzzy intelligent algorithm with a triangular membership function is implemented to calculate the control force and the Harmony Search Algorithm (HAS) is examined to optimize the actuator power. Also, the Fluid-Structure Interaction (FSI), the effect of added mass due to the accelerated motion of the body in the fluid, and the saturation of the actuator are considered. The results show the effectiveness of the proposed control system by reducing 20% and 50% of the maximum and RMS of the platform deck acceleration, respectively, over time.
Keywords: Jacket Platform, Active tuned mass damper, Harmony Search Algorithm, Fluid-Structure Interaction -
بهینه سازی توپولوژی سازه های گسسته بزرگ مقیاس، از چالش برانگیزترین مسائل بهینه سازی به شمار می روند. در این نوع بهینه سازی، هنگامی که سطح مقطع اعضا از میان مقادیر گسسته انتخاب می شوند، رسیدن به بهینه کلی دشوارتر می گردد. در این مقاله، روش بهینه سازی دومرحله ای نوینی جهت بهینه سازی توپولوژی سازه های گسسته بزرگ مقیاس (شبکه های دولایه)، با در نظر گرفتن قیود مختلف و با استفاده از الگوریتم جستجوی هارمونی (HSA) ارائه شده است. بدین منظور، ابتدا با استفاده از روش بهینه سازی تکاملی سازه ها (ESO)، یک آنالیز حساسیت جهت شناخت اعضای سازه ای مهم تر، انجام می شود. سپس نتایج این آنالیز حساسیت به نحوی مورد استفاده قرار می گیرد، که HSA بتواند با ایجاد یک جستجوی جهت دار در یک فضای طراحی کاهش یافته، توپولوژی بهینه شبکه های دولایه را بدست آورد. در روند بهینه سازی توپولوژی، وزن سازه کمینه می گردد بطوریکه قیود مسئله بهینه سازی شامل تنش اعضا و جابجایی گره ها و نیز ضریب لاغری اعضا ارضا گردند. همچنین، وجود و عدم وجود اعضای شبکه پایین و جانی و نیز سطح مقطع اعضای سازه بعنوان متغیرهای طراحی انتخاب شده است. حذف اعضای شبکه پایین و جانی، از طریق حذف گره های شبکه پایین انجام شده است. به منظور کاهش فضای طراحی، از تقارن سازه جهت حذف گروهی این گره ها استفاده می شود. نتایج عددی بدست آمده در این مقاله، کارایی روش دومرحله ای ارائه شده را در یافتن توپولوژی بهینه شبکه های دولایه نشان می دهند.کلید واژگان: سازه های گسسته، شبکه های دولایه، بهینه سازی توپولوژی، روش بهینه سازی تکاملی سازه ها، الگوریتم جستجوی هارمونیLarge-scale spatial skeletal structures belong to a special kind of 3D structures widely used in exhibition centers, supermarkets, sport stadiums, airports, etc., to cover large surfaces without intermediate columns. Space structures are often categorized as grids, domes and barrel vaults. Double layer grid structures are classical instances of prefabricated space structures and also the most popular forms which are frequently used nowadays.Topology optimization of large-scale skeletal structures has been recognized as one of the most challenging tasks in structural design. In topology optimization of these structures with discrete cross-sectional areas, the performance of meta-heuristic optimization algorithms can be increased if they are combined with continuous-based topology optimization methods. In this article, a hybrid methodology combining evolutionary structural optimization (ESO) and harmony search algorithm (HSA) methods is proposed for topologyoptimization of double layer grid structures subject to vertical load. In the present methodology, which is called ESO-HSA method, the size optimization of double layer grid structures is first performed by the ESO. Then, the outcomes of the ESO are used to improve the HSA. In fact, a sensitivity analysis is carried out using an optimization method (ESO) to determine more important members based on the cross-sectional areas of members. Then, the obtained optimum cross-sectional areas of members are used to enhance the HSA through two modifications. Structural weight is minimized against constraints on the displacements of nodes, internal stresses and element slenderness ratio. In topology optimization of double layer grid structures, the geometry of the structure, support locations and coordinates of nodes are fixed and this structure is assumed as a ground structure. Presence/absence of bottom nodes, and element cross-sectional areas are selected as design variables. In topology optimization of the ground structure, tabulating of nodes is carried out based on structural symmetry: this leads to reduce complexity of design space and nodes are removed in groups of 8, 4 or 1. The presence or absence of each node group is determined by a variable (topology variable) which takes the value of 1 and 0 for the two cases, respectively. The ground structure is assumed to be supported at the perimeter nodes of the bottom grid. Therefore, these supported nodes will not be removed from the ground structure. In order to achieve a practical structure, the existence of nodes in the top grid will not be considered as a variable. This causes the load bearing areas of top layer nodes to remain constant. Also, discrete variables are used to optimize the cross-sectional area of structural members. These variables are selected from pipe sections with specified thickness and outer diameter. Therefore, in topology optimization problem, the number of design variables is the summation of the number of compressive and tensile element types and the number of topology variables. The proposed approach is successfully tested in topology optimization problem of double layer grid structure. In particular, ESO-HSA is very competitive with other metaheuristic methods recently published in literature and can always find the best design overall. Also, it is determined that HSA method can find better answer in the topology optimization of large-scale skeletal structures, in comparison to optimum structures attained by the GSA and ICA.Keywords: Skeletal structures, Double layer grid structures, Topology optimization, Evolutionary structural optimization, harmony search algorithm
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International Journal of Optimization in Civil Engineering, Volume:8 Issue: 4, Autumn 2018, PP 587 -600Vulnerability assessment of structures encounter many uncertainties like seismic excitations intensity and response of structures. The most common approach adopted to deal with these uncertainties is vulnerability assessment through fragility functions. Fragility functions exhibit the probability of exceeding a state namely performance-level as a function of seismic intensity. A common approach is finding some response points of the fragility function and then fitting a typical probability distribution like lognormal through curve fitting estimation techniques. Maximum-likelihood approach is a fitting method to find the probability distribution parameters. Performing this approach for distributions like lognormal which is defined by just two parameters are straight forward while for more complicated distribution which are based on additional characterizing parameters is not feasible, since this approach is based on minimizing an error function through classic mathematical approaches like calculating partial derivations. An applicable modification is to add an efficient optimization approach to determine maximum-likelihood function. In this article, an optimization algorithm is proposed with maximum-likelihood-estimation and the results indicate the efficiency and feasibility of future developments in finding the most appropriate fragility function.Keywords: optimization, harmony search algorithm, vulnerability assessment, fragility function, maximum likelihood estimation
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In this research, a two-phase algorithm based on the artificial neural network (ANN) and a harmony search (HS) algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. The proposed method involves the generation of datasets to be used specifically for training by Finite Element analysis, to establish an ANN model using a proven ANN model in the reliability assessment process as an analyzer for structures, and finally estimate the reliability index and failure probability by using the HS algorithm, without any requirements for the explicit form of limit state function. The proposed algorithm is investigated here, and its accuracy and efficiency are demonstrated by using several numerical examples. The results obtained show that the proposed algorithm gives an appropriate estimate for the assessment of reliability of structures.Keywords: Artificial Neural Network, Failure Probability, Harmony Search Algorithm, Implicit Limit State Function, Reliability Index
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امروزه، مدل های دقیق رایانه ای کاربرد وسیعی در بهین هسازی مهندسی پیدا کرده اند. ارزیابی و محاسبه اکثر این مدل ها، نیازمند صرف زمان و هزینه زیادی است. در این مقاله یک روش جدید فرامد لسازی ترکیبی به منظور کاهش بار محاسباتی برای رسیدن به جواب بهینه در مسائل مدل سازی ارائه شده، این الگوریتم در ابتدا تعدادی نقاط نمونه ایجاد کرده، مقادیر پاسخ آنها را با استفاده از محاسبات دقیق به دست آورده و سپس مقدار پاسخ تقریبی نقاط جدید را به دست می آورد. در صورتی که پاسخ تقریبی به دست آمده در راستای همگرایی الگوریتم باشد، دست به محاسبه پاسخ دقیق آن خواهد زد. برای ارزیابی تاثیر این الگوریتم بر کاهش بار محاسباتی، چند مثال عددی استاندارد ارائه و نتایج آن با چند الگوریتم متداول بهین ه سازی همچون الگوریتم ژنتیک و کولونی مورچه ها مقایسه شده است. مقایسه نتایج نشان می دهد که این الگوریتم تاثیر زیادی بر کاهش بار محاسباتی و افزایش سرعت همگرایی دارد.کلید واژگان: بهینه سازی سازه، فرامدل سازی، الگوریتم جستجوی هارمونی، روش توزین عکس فاصلهHigh fidelity models are becoming increasingly common in engineering optimization. The computation burden is often caused by expensive analysis and simulation processes in order to reach a comparable level of accuracy as physical testing data. The metamodels are initially developed as surrogates of the expensive simulation process in order to improve the overall computation efficiency. This work presents a new multilevel optimization approach for multidisciplinary structural design optimization based on multi fidelity modeling to decrease computational effort. Such method is a composition of a statistical estimating method and a metaheuristic algorithm. A low fidelity analysis response determines if the high fidelity analysis should be done or not. As a result, most of unnecessary high fidelity calculation will be omitted. The empirical results show the new algorithm causes a significant decrease in computational load as well as increase in convergence rate. Keywords: Multi level optimization; Metamodeling; Harmony search algorithm; Inverse distance weighting model.Keywords: Multi level optimization, Metamodeling, harmony search algorithm, Inverse
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In this paper, a new hybrid Particle Swarm Optimization (PSO) and Harmony Search (HS) algorithm, denoted by PSOHS is presented. This hybrid algorithm is designed to improve the efficiency of the PSO and remove some of the disadvantages which reduce the capability of the PSO. The main problem of the PSO is the lack of balance between exploration and exploitation of the algorithm. Another problem is how to handle the violating particles from feasible search space without reduction in the performance of the algorithm. The problem of unbalanced exploration and exploitation is solved using linear varying inertia weight. The second problem is solved in some other algorithms via reproduction of the violating particles using the HS algorithm. In this paper, these two approaches are combined to achieve a more efficient algorithm for engineering design problems. To show the higher capability of this approach compared to other works, several benchmark engineering examples, which have been considered previously and solved utilizing a variety of optimization algorithms, is solved by the present hybrid algorithm. Results illustrate a desirable performance of the PSOHS in both obtaining lower weight and having a higher convergence rate.Keywords: Particle swarm optimization, harmony search algorithm, PSOHS, engineering optimization
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International Journal of Optimization in Civil Engineering, Volume:1 Issue: 3, Summer 2011, PP 485 -494The main aim of the present study is to propose a modified harmony search (MHS) algorithm for size and shape optimization of structures. The standard harmony search (HS) algorithm is conceptualized using the musical process of searching for a perfect state of the harmony. It uses a stochastic random search instead of a gradient search. The proposed MHS algorithm is designed based on elitism. In fact the MHS is a multi-staged version of the HS and in each stage a new harmony memory is created using the information of the previous stages. Numerical results reveal that the proposed algorithm is a powerful optimization technique with improved exploitation characteristics compared with the standard HS.Keywords: Shape optimization, harmony search algorithm, penalty functions, truss structure
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