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Few heuristic optimization algorithms to solve the multi-period fixed charge production-distribution problem | ||
| Journal of Computational & Applied Research in Mechanical Engineering (JCARME) | ||
| مقاله 2، دوره 1، شماره 2، شهریور 2012، صفحه 77-87 اصل مقاله (447.53 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22061/jcarme.2012.26 | ||
| نویسندگان | ||
| N. Balaji* 1؛ N. Jawahar2 | ||
| 1Department of Mechanical Engineering,Sri Krishna College of Engineering and Technology, Coimbatore 641 008, India | ||
| 2Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai 625 015, India | ||
| تاریخ دریافت: 14 شهریور 1390، تاریخ بازنگری: 25 آبان 1390، تاریخ پذیرش: 01 آذر 1390 | ||
| چکیده | ||
| This paper deals with a multi-period fixed charge production-distribution problem associated with backorder and inventories. The objective is to determine the size of the shipments from each supplier and backorder and inventories at each period, so that the total cost incurred during the entire period towards production, transportation, backorder and inventories is minimised. A 0-1 mixed integer programming problem is formulated. Genetic algorithm based population search heuristic, Simulated annealing based neighbourhood search heuristic and Equivalent variable cost based simple heuristic are proposed to solve the formulation. The proposed methodologies are evaluated by comparing their solutions with the lower bound solutions. The comparisons reveal that Genetic algorithm and Simulated annealing algorithm generate better solutions than the Equivalent variable cost solutions and are capable of providing solutions close to the lower bound value of the problems. | ||
| کلیدواژه‌ها | ||
| Multi-period fixed charge problem؛ 0-1 mixed integer programming problem؛ Genetic Algorithm؛ Simulated annealing algorithm؛ Equivalent variable cost | ||
| مراجع | ||
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[1] C. D. Flippo and G. Finke, “An integrated model for an industrial production- distribution problem,” IIE Transactions, Vol. 33, pp. 705-715, (2001).
[2] P. Chandra, and M. L. Fisher., “Coordination of production and transportation planning,” European Journal of Operational Research, Vol. 72, pp. 503-517,(1994).
[3] N. Rizk, A. Martel, S. D. Amours, “Synchronized production–transportation planning in a Single-plant multi-destination network,” Journal of the Operational Research Society, Vol.59, pp.90-104, (2008).
[4] D. Kim, P. M. Pardalos, “ A solution approach to the fixed charge network flow problem using a dynamic slope scaling procedure,” Operations Research Letter, Vol. 24, pp. 195-203 ,(1999).
[5] N. Haq, Prem Vrat, and Arun Kanda, “An integrated production-distribution model for manufacture of urea: a case,” International Journal of Production Economics, Vol. 39, pp. 39-49, (1991).
[6] G. Barbarosogluand and D. Ozgur, “Hierarchical design of an integrated production and 2-echelon transportation system,” European Journal of Operational Research, Vol. 118, pp. 464- 484, (1999).
[7] J. U. Kim, and Y. D. Kim, “A Lagrangian relaxation approach to multi-period inventory/distribution planning,” Journal of the Operational Research Society, Vol.51, pp. 364-370, (2000).
[8] P. Kaminsky and D. Simchi-Levi, “Production and transportation lot sizing in a two stage supply chain,” IIE Transactions, Vol.35, pp. 1065-1075, (2003).
[9] Y. B. Park, “An integrated approach for production and distribution planning in supply chain management,” International Journal of Production Research, Vol. 43(6), pp. 1205-1224, (2005).
[10] T. F. Abdelmaguid and M. M. Dessouky, “A Genetic algorithm approach to the integrated inventory-distribution problem,” International Journal of Production Research, Vol. 44 (21), pp. 4455-4464, (2006).
[11] F. Z. Sargut and H. E. Romeijn, “Capacitated production and subcontracting in a serial supply chain,” IIE Transactions, Vol. 39, pp. 1031-1043, (2007).
[12] A. S. Safaei, S. M. Moattar Husseini, R. Z. Farahani, F. Jolai and S. H. Ghodsypour, “Integrated multi-site production-distribution planning in supply chain by hybrid modeling,” International Journal of Production Research, Vol.48 (14), pp. 4043-4069, (2010).
[13] D. E. Goldberg, “Genetic algorithms in search, Optimization and Machine Leaning,” Addison Wesley Limited: U.S.A, (2000).
[14] M. Gen, A. Kumar, J. R. Kim, “Recent network design techniques using evolutionary algorithms,” International Journal of Production Economics, Vol. 98, pp. 251-261.
[15] W. Dullaert, M. Sevaux, K. Sorensen, “Applications of Meta-heuristics,” European Journal of Operational Research, Vol. 179, pp. 601- 604, (2007).
[16] S. Parthasarathy and C. Rajendran, , “An experimental evaluation of heuristics for scheduling in a real life flow shop with sequence-dependent set up time of jobs,” International Journal of Production Economics, Vol. 49, pp. 255-263 ,(1997).
[17] S.G. Ponnambalam, N. Jawahar, and P. Aravindan, “A Simulated Annealing Algorithm for Job Shop Scheduling,” Production Planning and Control, Vol.10, pp. 767-777, (1999).
[18] V. Jayaraman and A. Ross, “A simulated annealing methodology to transportation network design and management,” European Journal of Operational Research, Vol.144, pp 629-645, (2003).
[19] B. Suman and P. Kumar ,A survey of simulated annealing as a tool for single and multi-objective optimization,” Journal of Operational Research Society, Vol. 57, pp. 1143-1160, (2006).
[20] A. N. Balaji and N. Jawahar, “A Simulated Annealing Algorithm for a two-stage fixed charge distribution problem of a Supply Chain,” International Journal of Operational Research, Vol. 7(2), pp. 192-215, (2010).
[21] S. A. Mansouri, “A simulated annealing approach to a bi-criteria sequencing problem in a two-stage supply chain,” Computers & Industrial Engineering, Vol.50, pp. 105-119, (2006).
[22] U.S. Palekar, M. H. Karwan, and S. Zionts, “A branch-and-bound method for the fixed charge transportation problem,” Management Science, 36 (9), pp. 1092-1105, (1990). | ||
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