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Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain

Author

Listed:
  • Henning Strubelt

    (Institute of Logistics and Material Handling Systems, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany)

  • Sebastian Trojahn

    (Institute of Logistics and Material Handling Systems, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany)

  • Sebastian Lang

    (Institute of Logistics and Material Handling Systems, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany)

  • Abdulrahman Nahhas

    (Institute of Logistics and Material Handling Systems, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany)

Abstract

The general goal of waste management is to conserve resources and avoid negative environmental impacts. This paper deals with the optimization of logistics processes at an underground waste storage site by means of solving scheduling issues and reducing setup times, with the help of a simulation model. Specific to underground waste storage is the fact that it is often only a side business to actual mining. With limited capacity and resources, all legal requirements must be met, while the business should still be profitable. This paper discusses the improvement of a logistical system’s performance using machine scheduling approaches with the support of a plant simulation model. The process sequence is determined by means of a priority index. Genetic algorithms are then applied to improve the priority index to further increase performance. Results of the simulation model show that the performance of the logistics system can be increased by up to 400 percent, ensuring adequate system performance for current as well as future demand without changes to the system’s capacities and resources.

Suggested Citation

  • Henning Strubelt & Sebastian Trojahn & Sebastian Lang & Abdulrahman Nahhas, 2018. "Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain," Logistics, MDPI, vol. 2(3), pages 1-11, July.
    • Handle: RePEc:gam:jlogis:v:2:y:2018:i:3:p:12-:d:158141
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    References listed on IDEAS

    as
    1. Gupta, Sushil K & Kyparisis, Jerzy, 1987. "Single machine scheduling research," Omega, Elsevier, vol. 15(3), pages 207-227.
    2. Gupta, Jatinder N.D. & Stafford, Edward Jr., 2006. "Flowshop scheduling research after five decades," European Journal of Operational Research, Elsevier, vol. 169(3), pages 699-711, March.
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