Flexible Workshop Scheduling Decision Based on Heuristic Algorithm
Science Discovery
Volume 6, Issue 6, December 2018, Pages: 521-528
Received: Dec. 11, 2018; Published: Dec. 12, 2018
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Authors
Xuanzheng Wang, Institute of Information and Electronics, Beijing Institute of Technology, Beijing, China
Haoyang Luo, Institute of Information and Electronics, Beijing Institute of Technology, Beijing, China
Juntang Zhang, Institute of Information and Electronics, Beijing Institute of Technology, Beijing, China
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Abstract
In view of the realistic scenes in the flexible shop scheduling problem, the models are abstracted from different machining processes and machine tool failures. For this NP-hard problem, consider a variety of flexible scheduling heuristics, compare their global search and local search performance and discuss the adaptability of different scenarios. Scenario 1 uses a tabu search algorithm and defines the scope of each decision based on analysis and practice.;Scenario 2 analyzes the problems of CNC tool change, loading and unloading matching, process information preservation, etc. The algorithm selection is based on the comparative discussion of model one, and innovatively applies the tabu search algorithm idea to the recombination and mutation part of the genetic algorithm. The model can better encode the process information while ensuring strong local search ability, and adjust the search range of the model to solve the planning time convergence problem, and adjust the order to solve the "circular decision" problem in the model; Scenario 3 adds CNC random fault simulation, re-plans the decision model call time, and redesigns the process save decision of model two. In the model promotion, the algorithm of multi-RGV scheduling problem is discussed, and the applicability and efficiency of the model are clarified.
Keywords
Flexible Shop Scheduling, Tabu Search Algorithm, Genetic Algorithm
To cite this article
Xuanzheng Wang, Haoyang Luo, Juntang Zhang, Flexible Workshop Scheduling Decision Based on Heuristic Algorithm, Science Discovery. Vol. 6, No. 6, 2018, pp. 521-528. doi: 10.11648/j.sd.20180606.33
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