{"title":"A Genetic Algorithm Based Permutation and Non-Permutation Scheduling Heuristics for Finite Capacity Material Requirement Planning Problem","authors":"Watchara Songserm, Teeradej Wuttipornpun","volume":123,"journal":"International Journal of Industrial and Manufacturing Engineering","pagesStart":655,"pagesEnd":661,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10006733","abstract":"
This paper presents a genetic algorithm based permutation and non-permutation scheduling heuristics (GAPNP) to solve a multi-stage finite capacity material requirement planning (FCMRP) problem in automotive assembly flow shop with unrelated parallel machines. In the algorithm, the sequences of orders are iteratively improved by the GA characteristics, whereas the required operations are scheduled based on the presented permutation and non-permutation heuristics. Finally, a linear programming is applied to minimize the total cost. The presented GAPNP algorithm is evaluated by using real datasets from automotive companies. The required parameters for GAPNP are intently tuned to obtain a common parameter setting for all case studies. The results show that GAPNP significantly outperforms the benchmark algorithm about 30% on average.<\/p>\r\n","references":"[1]\tW. H. M. Zijm, and R. Buitenhek, \u201cCapacity planning and lead time management,\u201d International Journal of Production Economics. vol. 46, pp. 165-179, 1996.\r\n[2]\tM. Taal, and J. C. Wortmann, \u201cIntegrating MRP and finite capacity planning,\u201d Production Planning & Control, vol. 8, no. 3, pp. 245-251, 1997.\r\n[3]\tP. C. Pandey, P. Yenradee, S. Archariyapruek, \u201cA finite capacity material requirement planning system,\u201d Production Planning & Control, vol. 11, no. 2, pp.113\u2013121, 2000.\r\n[4]\tP. B., Nagendra, and S. K. Das, \u201cFinite capacity scheduling method for MRP with lot size restrictions,\u201d International Journal of Production Research, vol. 39 no. 8, pp. 1603-1623, 2001.\r\n[5]\tT. Wuttipornpun, and P. Yenradee, \u201cDevelopment of finite capacity material requirement planning system for assembly operations,\u201d Production Planning & Control, vol. 15, no. 4, pp. 534-549, 2004.\r\n[6]\tJ. Mula, R. Poler, J. P. Garcia, \u201cMRP with flexible constraints: A fuzzy mathematical programming approach.\u201d Fuzzy Sets and Systems, vol. 157, no. 1, pp. 74-97, 2006.\r\n[7]\tM. Vanhoucke, and D. Debels, A finite-capacity production scheduling procedure for a Belgian steel company. International Journal of Production Research, vol. 47 no. 3, pp. 561\u2013584, 2009.\r\n[8]\tC. \u00d6zt\u00fcrk, A. M. \u00d6rnek \u201cCapacitated lot sizing with linked lots for general product structures in job shops,\u201d Computers & Industrial Engineering vol. 58, no. 1, pp. 151\u2013164, 2010.\r\n[9]\tK. Th\u00f6rnblad, A-B. Str\u00f6mberg, M. Patriksson, and T. Almgren, \u201cScheduling optimisation of a real flexible job shop including fixture availability and preventive maintenance,\u201d European Journal of Industrial Engineering, vol. 9, no. 1, pp. 126\u2013145, 2015.\r\n[10]\tC. Moon, Y. Seo, Y. Yum, and M. Gen, \u201cAdaptive genetic algorithm for advanced planning in manufacturing supply chain,\u201d Journal of Intelligent Manufacturing, vol. 17, no. 4, pp. 509-522, 2006.\r\n[11]\tH. Kim, H. I. Jeong, and J. Park, \u201cIntegrated model for production planning and scheduling in a supply chain using benchmarked genetic algorithm,\u201d International Journal of Advanced Manufacturing Technology, vol. 39, no. 11, pp. 1207\u20131226, 2008.\r\n[12]\tM. H. F. Rahman, R. Sarkerm and D. Essam, \u201cA real-time order acceptance and scheduling approach for permutation flow shop problems,\u201d European Journal of Operational Research, vol. 247, no. 2, pp. 488-503, 2015.\r\n[13]\tM. Zandieh, and N. Karimi, \u201cAn adaptive multi-population genetic algorithm to solve the multi-objective group scheduling problem in hybrid flexible flowshop with sequence-dependent setup times,\u201d Journal of Intelligent Manufacturing, vol. 22, no. 6, pp. 979-989, 2011.\r\n[14]\tP-C. Chang, W-H. Huang, J-L. Wu, and T. C. E. Cheng, \u201cA block mining and re-combination enhanced genetic algorithm for the permutation flowshop scheduling problem,\u201d International Journal of Production Economics, vol. 141, no. 1, pp. 45-55, 2013.\r\n[15]\tT. Wuttipornpun, and P. Yenradee, \u201cFinite capacity material requirement planning system for assembly flow shop with alternative work centres,\u201d International Journal of Industrial and Systems Engineering, vol. 18, no. 1, pp. 95\u2013124, 2014.\r\n[16]\tR. Vanchipur, and R. Sridharan, \u201cDevelopment and analysis of hybrid genetic algorithms for flow shop scheduling with sequence dependent setup time\u201d International Journal of Services and Operations Management, vol. 17, no. 2, 2014.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 123, 2017"}