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Inventory Based Bi-Objective Flow Shop Scheduling Model and Its Hybrid Genetic Algorithm

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  • Ren Qing-dao-er-ji
  • Yuping Wang

Abstract

Flow shop scheduling problem is a typical NP-hard problem, and the researchers have established many different multi-objective models for this problem, but none of these models have taken the inventory capacity into account. In this paper, an inventory based bi-objective flow shop scheduling model was proposed, in which both the total completion time and the inventory capacity were as objectives to be optimized simultaneously. To solve the proposed model more effectively, we used a tailor-made crossover operator, and mutation operator, and designed a new local search operator, 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 indicated the effectiveness of the proposed algorithm.

Suggested Citation

  • Ren Qing-dao-er-ji & Yuping Wang, 2013. "Inventory Based Bi-Objective Flow Shop Scheduling Model and Its Hybrid Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, April.
    • Handle: RePEc:hin:jnlmpe:976065
    DOI: 10.1155/2013/976065
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    Cited by:

    1. Pannee Suanpang & Pitchaya Jamjuntr & Kittisak Jermsittiparsert & Phuripoj Kaewyong, 2022. "Tourism Service Scheduling in Smart City Based on Hybrid Genetic Algorithm Simulated Annealing Algorithm," Sustainability, MDPI, vol. 14(23), pages 1-21, December.

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