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Online Optimization of a Color Sorting Assembly Buffer Using Ant Colony Optimization

In: Operations Research Proceedings 2007

Author

Listed:
  • Stephan A. Hartmann

    (Siemens AG, Corporate Technology)

  • Thomas A. Runkler

    (Siemens AG, Corporate Technology)

Abstract

In this paper we present an ant based approach for the problem of scheduling a color sorting assembly buffer online. In the automotive industry, all car bodies are painted at a paint shop, where it is important that the number of color changes is minimized. The car bodies on the assembly line are unsorted with respect to their color, thus a color sorting assembly buffer may be used to reduce the number of color changes. The problem of finding an optimal strategy for controlling a color sorting assembly buffer (CSAB) consists of two closely related sub-problems: the color retrieval problem (CRP) and the color storage problem (CSP). Their combination, the color storage and retrieval problem (CSRP) is NP-complete, existing methods are not applicable on larger problems. In this paper we introduce two ant colony optimization (ACO) algorithms that probabilistically solve the CRP and the CSP, respectively. They significantly outperform the conventional rule based approach.

Suggested Citation

  • Stephan A. Hartmann & Thomas A. Runkler, 2008. "Online Optimization of a Color Sorting Assembly Buffer Using Ant Colony Optimization," Operations Research Proceedings, in: Jörg Kalcsics & Stefan Nickel (ed.), Operations Research Proceedings 2007, pages 415-420, Springer.
    • Handle: RePEc:spr:oprchp:978-3-540-77903-2_64
    DOI: 10.1007/978-3-540-77903-2_64
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    Cited by:

    1. Rui Zhang, 2017. "Environment-Aware Production Scheduling for Paint Shops in Automobile Manufacturing: A Multi-Objective Optimization Approach," IJERPH, MDPI, vol. 15(1), pages 1-32, December.

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