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Hybrid Algorithm Based on an Estimation of Distribution Algorithm and Cuckoo Search for the No Idle Permutation Flow Shop Scheduling Problem with the Total Tardiness Criterion Minimization

Author

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  • Zewen Sun

    (Key Laboratory of Advanced Control and Optimization for Chemical Process, East China University of Science and Technology, Ministry of Education, Shanghai 200237, China)

  • Xingsheng Gu

    (Key Laboratory of Advanced Control and Optimization for Chemical Process, East China University of Science and Technology, Ministry of Education, Shanghai 200237, China)

Abstract

The no idle permutation flow shop scheduling problem (NIPFSP) is a popular NP-hard combinatorial optimization problem, which exists in several real world production processes. This study proposes a novel hybrid estimation of the distribution algorithm and cuckoo search (CS) algorithm (HEDA_CS) to solve the NIPFSP with the total tardiness criterion minimization. The problem model is built on the basis of the starting and ending time point of each job. A discrete solution representation method is applied in HEDA_CS to increase the operation efficiency. A novel probability matrix build method is also designed within the knowledge of the processing time matrix. The partially-mapped crossover operation works effectively during the CS phase. A suitable knowledge-based local search is also designed in the HEDA_CS to balance the exploitation and exploration. Finally, many simulations based on the new hard Ruiz benchmarks are conducted. Computational results demonstrate the effectiveness of the proposed HEDA_CS.

Suggested Citation

  • Zewen Sun & Xingsheng Gu, 2017. "Hybrid Algorithm Based on an Estimation of Distribution Algorithm and Cuckoo Search for the No Idle Permutation Flow Shop Scheduling Problem with the Total Tardiness Criterion Minimization," Sustainability, MDPI, vol. 9(6), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:6:p:953-:d:100571
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    References listed on IDEAS

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    1. Ruiz, Ruben & Maroto, Concepcion, 2005. "A comprehensive review and evaluation of permutation flowshop heuristics," European Journal of Operational Research, Elsevier, vol. 165(2), pages 479-494, September.
    2. Pan, Quan-Ke & Ruiz, Rubén, 2014. "An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem," Omega, Elsevier, vol. 44(C), pages 41-50.
    3. Vallada, Eva & Ruiz, Rubén & Framinan, Jose M., 2015. "New hard benchmark for flowshop scheduling problems minimising makespan," European Journal of Operational Research, Elsevier, vol. 240(3), pages 666-677.
    4. Quan-Ke Pan & Ling Wang, 2008. "A novel differential evolution algorithm for no-idle permutation flow-shop scheduling problems," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 2(3), pages 279-297.
    5. Baraz, Daniel & Mosheiov, Gur, 2008. "A note on a greedy heuristic for flow-shop makespan minimization with no machine idle-time," European Journal of Operational Research, Elsevier, vol. 184(2), pages 810-813, January.
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    Cited by:

    1. Jin Huang & Liangliang Jin & Chaoyong Zhang, 2017. "Mathematical Modeling and a Hybrid NSGA-II Algorithm for Process Planning Problem Considering Machining Cost and Carbon Emission," Sustainability, MDPI, vol. 9(10), pages 1-18, September.

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