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Volume 299 - The 7th International Conference on Computer Engineering and Networks (CENet2017) - Session III -Information Theory
An Intelligent Method for Solving Flexible Job Shop Scheduling Problem
Q. Meng,* L. Zhang, Y. Fan, H. Luo, H. Zhao
*corresponding author
Full text: pdf
Pre-published on: 2017 July 17
Published on: 2017 September 06
Abstract
An efficient intelligent algorithm is proposed in this paper to solve the flexible job shop scheduling problem (FJSSP). The algorithm takes genetic algorithm (GA) as the main frame, and combines tabu search (TS) with simulated annealing (SA) to promote local search. The operation-based representation, novel crossover and mutation operation are introduced to
increase individual diversity. When the current solution exists in the tabu list, the algorithm performs local search incorporating TS and the SA method to explore the neighbourhood of the individuals. The experiments are carried out on 10 different scales instances and the results with other algorithms are compared. The results conclude that the proposed algorithm has advantages on both the quality and the time consuming which is effective to the actual FJSSP.
DOI: https://doi.org/10.22323/1.299.0050
Open Access
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