2019
DOI: 10.3390/app9163360
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Cooperative Threads with Effective-Address in Simulated Annealing Algorithm to Job Shop Scheduling Problems

Abstract: This paper presents a parallel algorithm applied to the job shop scheduling problem (JSSP). The algorithm generates a set of threads, which work in parallel. Each generated thread, executes a procedure of simulated annealing which obtains one solution for the problem. Each solution is directed towards the best solution found by the system at the present, through a procedure called effective-address. The cooperative algorithm evaluates the makespan for various benchmarks of different sizes, small, medium, and l… Show more

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Cited by 6 publications
(3 citation statements)
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“…To reduce the time in which the optimized relaxation factors of the Driven-Cavity problem are obtained, work will be done to parallelize the SA algorithm using parallelization independent of SA, generating multiple executions of SA in parallel as applied in [24], or performing a parallelization of the metropolis cycle as applied in [25]. Either of the two parallelization techniques used will allow a reduction in SA execution time of over 80%, when using 10 central processing units for the execution of the SA algorithm designed to work in parallel.…”
Section: Future Workmentioning
confidence: 99%
“…To reduce the time in which the optimized relaxation factors of the Driven-Cavity problem are obtained, work will be done to parallelize the SA algorithm using parallelization independent of SA, generating multiple executions of SA in parallel as applied in [24], or performing a parallelization of the metropolis cycle as applied in [25]. Either of the two parallelization techniques used will allow a reduction in SA execution time of over 80%, when using 10 central processing units for the execution of the SA algorithm designed to work in parallel.…”
Section: Future Workmentioning
confidence: 99%
“…However, the solution quantity will increase exponentially in large-scale combinatorial optimization problems. To solve such problems efficiently, many heuristic algorithms have been studied, including the genetic algorithm (GA) [20][21][22], the ant colony algorithm [23,24], the simulated annealing algorithm [25][26][27], and the tabu search algorithm [28,29].…”
Section: Introductionmentioning
confidence: 99%
“…Zhou et al [ 18 ] presented a hybrid social-spider optimization algorithm with a differential mutation (SSO-DM) operator to solve JSSP. Cruz-Chávez et al [ 19 ] proposed a parallel algorithm that generated a set of parallel working threads, where each thread performed a simulated annealing process to solve JSSP. For JSSP, Pongchairerks [ 20 ] proposed a new two-level meta-heuristic algorithm composed of an upper-level algorithm and a lower-level algorithm.…”
Section: Introductionmentioning
confidence: 99%