Material Scheduling with Storage Windows Based on Modified Particle Swarm Algorithm for Material Manufacturing System

Xin Min Zhang; Su Zhang

doi:10.4028/www.scientific.net/AMM.252.343

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 252Material Scheduling with Storage Windows Based on...

Material Scheduling with Storage Windows Based on Modified Particle Swarm Algorithm for Material Manufacturing System

Abstract:

In order to solve the logistics problems in replenishment delay, low efficiency, high delivery time cost occurred on the side of automobile assembly line, a combination of “Workstation - Supermarket” is proposed to optimize vehicle scheduling. Storage windows are firstly proposed to replace pervious time windows. In this paper, based on analyzing the JIT material flow of line side, an optimization scheduling model with storage windows is established by taking the minimum of total delivery time as the objective function. A modified particle swarm optimization algorithm (MPSO) is introduced to solve the model. The result of simulation showed that the MPSO has superior performance on the proposed vehicle routing problem with storage windows (VRPSW). Furthermore, it is shown that MPSO is more efficiently on VRP in material manufacturing system.

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Periodical:

Applied Mechanics and Materials (Volume 252)

Pages:

343-348

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.252.343

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Online since:

December 2012

Authors:

Xin Min Zhang, Su Zhang

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JIT, MPSO, VRPSW, Workstation-Supermarket

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References

[1] Ding FY, Sun H (2004) Sequence alteration and restoration related to sequenced parts delivery on an automobile mixed-model assembly line with multiple departments. Int. J Prod Res 42(8): 1525–1543.

DOI: 10.1080/00207540310001645156

Google Scholar

[2] Roodbergen KJ, VisIFA (2009) A survey of literature on automated storage and retrieval systems. Eur J Oper Res 194(2): 343–362.

Google Scholar

[3] Brandao J. A search algorithm for the open vehicle routing problem[J]. European Journal of Operational Research, 2004, 157: 552-564.

DOI: 10.1016/s0377-2217(03)00238-8

Google Scholar

[4] Ayed S, Imtiaz S, Sabah A-M. Particle swarm optimization for task assignment problem. Microprocessors and Microsystems, 2002, 26: 363-371.

DOI: 10.1016/s0141-9331(02)00053-4

Google Scholar

[5] Meyr H (2004) Supply chain planning in the German automotive industry. OR Spectr 26(4): 447–470.

Google Scholar

[6] Hoong C L, Melvyn S, Kwong M T. Vehicle routing problem with time windows and a limited number of vehicles. European Journal of Operational Research, 2003, 148: 559- 569.

DOI: 10.1016/s0377-2217(02)00363-6

Google Scholar

[7] Chiang W. C, Russell R.A. Simulated annealing metaheuristies for the vehicle routing problem with time windows. Annals of Operations Researeh, 1996 (63): 3~27.

DOI: 10.1007/bf02601637

Google Scholar

[8] Donati AV, Montemanni R, Casagrande N, Rizzoll AE, Gambardella LM. Time dependent vehicle routing problems with a multi ant colony system. European Journal of Operational Research, 2008, 185(3) ：1174~1191.

DOI: 10.1016/j.ejor.2006.06.047

Google Scholar