نتایج جستجو برای: genetic algorithm and simulated annealing algorithm
تعداد نتایج: 16980195 فیلتر نتایج به سال:
Software testing is an important stage in the software development process, which key to ensure quality and improve reliability. fault localization most part of testing. In this paper, problem modeled as a combinatorial optimization problem, using function call path starting point. A heuristic search algorithm based on hybrid genetic simulated annealing used locate defects. Experimental results...
Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...
The forward kinematics of the 6-6 leg parallel manipulator is solved using hybrid meta-heuristic techniques in which the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results are compared with the standard simulated annealing and genetic algorithm. It shows that the standard simulated annealing algorithm outperforms standard genetic algorithm in terms ...
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.
due to the limiting workspace of parallel manipulator and regarding to finding the trajectory planning of singularity free at workspace is difficult, so finding a best solution that can develop a technique to determine the singularity-free zones in the workspace of parallel manipulators is highly important. in this thesis a simple and new technique are presented to determine the maximal singula...
The main goal of this work is to propose a way for combined use of two nontraditional algorithms by solving topological problems on telecommunications concentrator networks. The algorithms suggested are the Simulated Annealing algorithm and the Genetic Algorithm. The Algorithm of Simulated Annealing unifies the well known local search algorithms. In addition Simulated Annealing allows acceptati...
In this paper, the author proposes the application of a genetic algorithm and simulated annealing to solve the network planning problem. Compared with other optimisation methods, genetic algorithm and simulated annealing are suitable for traversing large search spaces since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will ...
Job Shop Scheduling Problem (JSSP) is an optimization problem in which ideal jobs are assigned to resources at particular times. In recent years many attempts have been made at the solution of JSSP using a various range of tools and techniques such as Branch and Bound and Heuristics algorithms. This paper proposed a new algorithm based on Genetic Algorithm (GA), Tabu Search (TS) and Simulated A...
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