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Hybrid Meta-Heuristics for Robust Scheduling

Author

Listed:
  • Surico, M.
  • Kaymak, U.
  • Naso, D.
  • Dekker, R.

Abstract

The production and delivery of rapidly perishable goods in distributed supply networks involves a number of tightly coupled decision and optimization problems regarding the just-in-time production scheduling and the routing of the delivery vehicles in order to satisfy strict customer specified time-windows. Besides dealing with the typical combinatorial complexity related to activity assignment and synchronization, effective methods must also provide robust schedules, coping with the stochastic perturbations (typically transportation delays) affecting the distribution process. In this paper, we propose a novel metaheuristic approach for robust scheduling. Our approach integrates mathematical programming, multi-objective evolutionary computation, and problem-specific constructive heuristics. The optimization algorithm returns a set of solutions with different cost and risk tradeoffs, allowing the analyst to adapt the planning depending on the attitude to risk. The effectiveness of the approach is demonstrated by a real-world case concerning the production and distribution of ready-mixed concrete.

Suggested Citation

  • Surico, M. & Kaymak, U. & Naso, D. & Dekker, R., 2006. "Hybrid Meta-Heuristics for Robust Scheduling," ERIM Report Series Research in Management ERS-2006-018-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:7644
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    References listed on IDEAS

    as
    1. Gendreau, Michel & Laporte, Gilbert & Seguin, Rene, 1996. "Stochastic vehicle routing," European Journal of Operational Research, Elsevier, vol. 88(1), pages 3-12, January.
    2. Kenneth R. Baker & Gary D. Scudder, 1990. "Sequencing with Earliness and Tardiness Penalties: A Review," Operations Research, INFORMS, vol. 38(1), pages 22-36, February.
    3. Naso, David & Surico, Michele & Turchiano, Biagio & Kaymak, Uzay, 2007. "Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2069-2099, March.
    4. Naso, D. & Surico, M. & Turchiano, B. & Kaymak, U., 2004. "Genetic Algorithms in Supply Chain Scheduling of Ready-Mixed Concrete," ERIM Report Series Research in Management ERS-2004-096-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Michel Gendreau & Gilbert Laporte & René Séguin, 1996. "A Tabu Search Heuristic for the Vehicle Routing Problem with Stochastic Demands and Customers," Operations Research, INFORMS, vol. 44(3), pages 469-477, June.
    6. Jones, D. F. & Mirrazavi, S. K. & Tamiz, M., 2002. "Multi-objective meta-heuristics: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 137(1), pages 1-9, February.
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    Cited by:

    1. Al-Hinai, Nasr & ElMekkawy, T.Y., 2011. "Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm," International Journal of Production Economics, Elsevier, vol. 132(2), pages 279-291, August.

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    More about this item

    Keywords

    Meta-Heuristics; Multi-Objective Genetic Optimization; Robust Scheduling; Supply Networks;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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