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A Surrogate Model-Based Hybrid Approach for Stochastic Robust Double Row Layout Problem

Author

Listed:
  • Xing Wan

    (School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
    Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing 100876, China)

  • Xing-Quan Zuo

    (School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
    Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing 100876, China)

  • Xin-Chao Zhao

    (School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Abstract

The double row layout problem is to arrange a number of machines on both sides of a straight aisle so as to minimize the total material handling cost. Aiming at the random distribution of product demands, we study a stochastic robust double row layout problem (SR-DRLP). A mixed integer programming (MIP) model is established for SR-DRLP. A surrogate model is used to linearize the nonlinear term in the MIP to achieve a mixed integer linear programming model, which can be readily solved by an exact method to yield high-quality solutions (layouts) for small-scale SR-DRLPs. Furthermore, we propose a hybrid approach combining a local search and an exact approach (LS-EA) to solve large-scale SR-DRLPs. Firstly, a local search is designed to optimize the machine sequences on two rows and the clearance from the most left machine on row 1 to the left boundary. Then, the exact location of each machine is further optimized by an exact approach. The LS-EA is applied to six problem instances ranging from 8 to 50 machines. Experimental results show that the surrogate model is effective and LS-EA outperforms the comparison approaches.

Suggested Citation

  • Xing Wan & Xing-Quan Zuo & Xin-Chao Zhao, 2021. "A Surrogate Model-Based Hybrid Approach for Stochastic Robust Double Row Layout Problem," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:15:p:1711-:d:598162
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    References listed on IDEAS

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