Title: Integrated marketing and operational decisions in remanufacturing of end-of-life products: model and hybrid solution algorithms

Authors: Seyed Ahmad Yazdian; Kamran Shahanaghi; Seyed Gholamreza Jalali Naini

Addresses: Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran; Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran ' Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran ' Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract: Remanufacturing is the ultimate form of product recovery with substantial economic and environmental advantages. However, despite growing popularity of remanufacturing, marketing issues such as pricing and warranty as well as accounting for the multi-component nature of remanufactured products are not adequately addressed in the literature. In this paper, we consider an independent remanufacturer (IR) who acquires multi-component end-of-life (EOL) products in different quality classes, remanufactures them and sells the recovered products bundled with warranty. The remanufacturer is interested in optimal acquisition prices of return products (known as cores) in different quality groups, the remanufacturing plan for each component, the selling price of the final product and the length of the warranty period to maximise its net profits. A mixed-integer nonlinear program is developed to address the problem where reliability and warranty issues are statistically incorporated into the model and PSO and GA algorithms hybridised with convex quadratic programming (CQP) are proposed for its solution.

Keywords: remanufacturing planning; pricing; warranty; reliability; particle swarm optimisation; PSO; end-of-life products; EOL products; quality groups; genetic algorithms; marketing decisions; operational decisions; modelling; mixed integer nonlinear programming; MINLP; convex quadratic programming; CQP.

DOI: 10.1504/IJOR.2017.083174

International Journal of Operational Research, 2017 Vol.29 No.1, pp.34 - 66

Received: 21 Aug 2013
Accepted: 27 Aug 2014
Published online: 22 Mar 2017 *

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