نتایج جستجو برای: simulated annealing sa algorithm
تعداد نتایج: 900894 فیلتر نتایج به سال:
این مقاله، عملکرد الگوریتم (Simulated Annealing) SA و (Genetic Algorithm) GA را در تعویض پیشگیرانه بهینه قطعات به منظور حداقل کردن زمان خوابیدگی بررسی میکند. به این منظور، تعدادی معیار ارزیابی برای تحلیل عملکرد این الگوریتمها تشریح شده تا با استفاده از آنها بتوان تصمیم گرفت که کدام الگوریتم را در تعویض پیشگیرانه قطعات میتوان بهکار برد.
abstract: in this paper, an exergy analysis approach is proposed for optimal design of distillation column by using simulated annealing algorithm. first, the simulation of a distillation column was performed by using the shortcut results and irreversibility in each tray was obtained. the area beneath the exergy loss profile was used as irreversibility index in the whole column. then, first opti...
Optimization problems for biomechanical systems have become extremely complex. Simulated annealing (SA) algorithms have performed well in a variety of test problems and biomechanical applications; however, despite advances in computer speed, convergence to optimal solutions for systems of even moderate complexity has remained prohibitive. The objective of this study was to develop a portable pa...
Simulated annealing (SA) algorithms can be modeled as time-inhomogeneous Markov chains. Much work on the convergence rate of simulated annealing algorithms has been well-studied. In this paper, we propose an adiabatic framework for studying simulated annealing algorithm behavior. Specifically, we focus on the problem of simulated annealing algorithms that start from an initial temperature T0 an...
Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative...
Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative...
this study is devoted to the formulation of the network design problem of one-way streets and the application of simulated annealing (sa) algorithm to solve this problem for a large real network. it discusses some points of views on one-way street networks, the objective function used for design, the way in which design constraints may be considered, and the traffic problems concerning one-way ...
Simulated Annealing and Genetic Algorithm are two well-known metaheuristic algorithms for combinatorial optimization. These two methods have also been used for solving constrained continuous problems. In this study, five constrained continuous problems have been solved both Simulated Annealing (SA) and Genetic Algorithm (GA). Optimum results have been compared with real optimum values obtained ...
modeling of fermentation processes is so complicated and uncertain; therefore it is necessary to provide a robust and appropriate dynamic optimization method. in order to obtain the maximum amount of yeast (saccharomyces cerevisiae), the bioreactor must be operated under optimal conditions. to determine substrate feeding in a fed-batch bioreactor, a simulated annealing (sa) approach was examine...
The permutation flow shop scheduling problem (PFSP) is one of the most well known and well studied production scheduling problems with strong industrial background. Most scheduling problems are combinatorial optimization problems which are too difficult to be solved optimally, and hence heuristics are used to obtain good solutions in a reasonable time. The specific goal of this paper is to inve...
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