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An ant colony system for enhanced loop-based aisle-network design

Asef Vaziri, A ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.ejor.2010.03.024
  3. Abstract:
  4. The purpose of this paper is to develop a global optimization model, simplification schemes, and a heuristic procedure for the design of a shortcut-enhanced unidirectional loop aisle-network with pick-up and drop-off stations. The objective is to minimize the total loaded and empty trip distances. This objective is the main determinant for the fleet size of the vehicles, which in turn is the driver of the total life-cycle cost of vehicle-based unit-load transport systems. The shortcut considerably reduces the length of the trips while maintaining the simplicity of the system. The global model solves simultaneously for the loop design, stations' locations and shortcut design. We then develop two simplifications each containing two serial phases. Phase-1 of the first simplification step focuses on both loaded and empty trips, while that of the second simplification focuses only on loaded trips. In phase-2, both designs are enhanced with a shortcut to minimize both loaded and empty trip distances. The quality and efficiency of the three alternative designs are tested for a set of problems with different layout size and product mix. While the solution time of the second simplification procedure is a small percentage of the global formulation, it generates satisfactory solutions. On this foundation, we then develop a heuristic procedure to replace phase-1 of the second simplification. The heuristic procedure is using ant colony system to generate feasible solutions and then we implement a local search algorithm to improve the results. The heuristic algorithm quickly generates close to optimal solutions for phase-1 of the second simplification. By applying phase-2 of the this second simplification on a set of loops generated by the heuristic, close to optimal solutions are also quickly obtained for the global model
  5. Keywords:
  6. Automated guided vehicle systems ; Facility logistics ; Vehicle based material transport systems ; Ant-colony optimization ; Automated guided vehicle system ; Facility layout ; Material handling ; Material transport systems ; Artificial intelligence ; Design ; Fleet operations ; Global optimization ; Heuristic algorithms ; Heuristic methods ; Learning algorithms ; Materials handling equipment ; Optimal systems ; Optimization ; Plant layout ; Printing machinery ; Vehicles ; Materials handling
  7. Source: European Journal of Operational Research ; Volume 207, Issue 1 , 2010 , Pages 110-120 ; 03772217 (ISSN)
  8. URL: http://www.sciencedirect.com/science/article/pii/S0377221710002237