Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30526
Production and Remanufacturing of Returned Products in Supply Chain using Modified Genetic Algorithm

Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, Y. Upendra Sravan

Abstract:

In recent years, environment regulation forcing manufactures to consider recovery activity of end-of- life products and/or return products for refurbishing, recycling, remanufacturing/repair and disposal in supply chain management. In this paper, a mathematical model is formulated for single product production-inventory system considering remanufacturing/reuse of return products and rate of return products follows a demand like function, dependent on purchasing price and acceptance quality level. It is useful in decision making to determine whether to go for remanufacturing or disposal of returned products along with newly produced products to satisfy a stationary demand. In addition, a modified genetic algorithm approach is proposed, inspired by particle swarm optimization method. Numerical analysis of the case study is carried out to validate the model.

Keywords: Production, Genetic Algorithm, Particle Swarm Optimization, Remanufacturing

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058203

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1362

References:


[1] A. M. A. ElSaadany, M. Y. Jaber, "A production/remanufacturing inventory model with price and quality dependant return rate," Computers & Industrial Engineering, vol. 58, pp. 352-362, 2010.
[2] U. Merschmann, U. W. Thonemann, "Supply chain flexibility, uncertainty and firm performance: An empirical analysis of German manufacturing firms." Int. J. Production Economics, vol.130, pp. 43- 53, 2011.
[3] Yanzhi. Li, Mark. Daskin, Saif. Benjaafar, "Carbon Footprint and the Management of Supply Chains: Insights from Simple Models." January 25, 2010.
[4] Balan. Sundarakani, Robert. deSouza, Mark. Goh, Stephan M. Wagner, Sushmera. Manikandan, "Modeling carbon footprints across the supply chain." Int. J. Production Economics, vol. 128, pp.43-50, 2010.
[5] E.U. Olugu, K.Y. Wong, A. M. Shaharoun, "Development of key performance measures for the automobile green supply chain." Resources, Conservation and Recycling, 2010.
[6] J.Kennedy, and R.C.Eberhart, "Particle swarm optimization", In Proceedings of the IEEE international conference on neural networks, vol. 4, pp. 1942-1948, NJ: IEEE Service Center, Piscataway, 1995.
[7] J. Kennedy, and W.Spears, "Matching algorithms to problems: An experimental test of the particle swarm and some genetic algorithms on the multimodal problem generator." In Proceedings of the IEEE international conference on evolutionary computation, pp.78-83, Anchorage, Alaska, 1998.
[8] Adam. Heying, Whitney. Sanzero. "A Case Study of Wal-Mart-s Green Supply Chain Management," Operations Management, MGT 520, May 4, 2009.