Inventory based two-objective job shop scheduling model and its hybrid genetic algorithm

Authors:
Ren Qing-Dao-Er-Ji;Yuping Wang;Xiaoli Wang
Affiliations:
School of Computer Science and Technology, School of Science, Xidian University, Xi'an, 710071, China;School of Computer Science and Technology, School of Science, Xidian University, Xi'an, 710071, China;School of Computer Science and Technology, School of Science, Xidian University, Xi'an, 710071, China
Venue:
Applied Soft Computing
Year:
2013

Citing 15
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Abstract

Job shop scheduling problem is a typical NP-hard problem. An inventory based two-objective job shop scheduling model was proposed in this paper, in which both the make-span (the total completion time) and the inventory capacity were as objectives and were optimized simultaneously. To solve the proposed model more effectively, some tailor made genetic operators were designed by making full use of the characteristics of the problem. Concretely, a new crossover operator based on the critical path was specifically designed. Furthermore, a local search operator was designed, which can improve the local search ability of GA greatly. Based on all these, a hybrid genetic algorithm was proposed. The computer simulations were made on a set of benchmark problems and the results demonstrated the effectiveness of the proposed algorithm.