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Journal of Industrial and Systems Engineering، جلد ۱۵، شماره ۴، صفحات ۹۱-۱۰۲
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عنوان انگلیسی Scheduling of production systems with the approach of meta-heuristic algorithms
چکیده انگلیسی مقاله The main goal of the research is production timing with the approach of meta-heuristic algorithms. First, the mathematical model of the production schedule was presented, and then the model was solved with the genetic algorithm. All types of genetic operators were considered at this stage, and an attempt was made to achieve better answers by choosing appropriate methods. The result of applying these targeted selection methods was the rapid convergence of the population. However, this fast convergence did not provide an optimal solution because it quickly converged all the people of the population to a local optimal solution and did not allow the algorithm to search more of the solution space. Therefore, contrary to expectations, the targeted selection methods without a suitable generation method did not improve the algorithm's efficiency. At this stage, the generation methods were considered; the optimal solution for big problems was also obtained by implementing the selection methods. By finding the appropriate generation method, it was observed that even the operators who did not have much ability to see close to optimal solutions succeeded in finding optimal solutions.
کلیدواژه‌های انگلیسی مقاله Production scheduling,workshop production system,Genetic Algorithm
نویسندگان مقاله Roza Montazeri Parchikolayi |
Ph.D. student, Department of Industrial Management, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

Seyed Ahmad Shayannia |
Department of Industrial Management, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

Amir Gholam Abri |
Department of Mathematics, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

Ebrahim Niknaqsh |
Department of Industrial Management, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

نشانی اینترنتی https://www.jise.ir/article_207866_1e80fde9c50ad6dd6a7171ef0ef30b94.pdf
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