نتایج جستجو برای: hybrid simulated annealing
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in today’s dynamic market, organizations must be adaptive to market fluctuations. in addition, studies show that material-handling cost makes up between 20 and 50 percent of the total operating cost. therefore, this paper considers the problem of arranging and rearranging, when there are changes in product mix and demand, manufacturing facilities such that the sum of material handling and rearr...
In this communication Simulated Annealing and Genetic Algorithms, are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuris...
In this paper scatter search algorithm has been hybridized with simulated annealing algorithm. Scatter search algorithm has some disadvantages which will be solved by using concepts of simulated annealing algorithm. Simulated annealing algorithm will provide scatter search algorithm with more of exploration for problem search space, this will increase ratio of getting optimal solutions. The hyb...
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 ...
Genetic Algorithm falls under the category of evolutionary algorithm that follows principles natural selection and genetics, where best adapted individuals in a population are more likely to survive reproduce, passing on their advantageous traits offsprings. Crossover is crucial operator genetic algorithms as it allows material two or combine create new individuals. Optimizing can potentially l...
In this paper, we examine the different measures of Fault Tolerance in a Distributed Simulated Annealing process. Optimization by Simulated Annealing on a distributed system is prone to various sources of failure. We analyse simulated annealing algorithm, its architecture in distributed platform and potential sources of failures. We examine the behaviour of tolerant distributed system for optim...
Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of ...
this paper addresses the vehicle routing problem with delivery time cost. this problem aims to find a set of routes of minimal total costs including the travelling cost and delivery time cost, starting and ending at the depot, in such a way that each customer is visited by one vehicle given the capacity of the vehicle to satisfy a specific demand. in this research, a hybrid metaheuristic approa...
Simulated annealing’s high computational intensity has stimulated researchers to experiment with various parallel and distributed simulated annealing algorithms for shared memory, message-passing, and hybrid-parallel platforms. MapReduce is an emerging distributed computing framework for large-scale data processing on clusters of commodity servers; to our knowledge, MapReduce has not been used ...
This paper proposes a new algorithm of a simulated annealing (SA): Parallel Simulated Annealing using Genetic Crossover (PSA/GAc). The proposed algorithm consists of several processes, and in each process SA is operated. The genetic crossover is used to exchange information between solutions at fixed intervals. While SA requires high computational costs, particularly in continuous problems, thi...
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