Abstract
We investigate joint optimisation of remanufacturing, pricing and warranty decision-making for end-of-life products. A novel mathematical–statistical model is proposed where decisions involve pricing of returned used products (cores), degree of their remanufacturing, selling price and the warranty period for the final remanufactured products. The virtual age reliability improvement approach is chosen to model the upgrading of the cores to higher quality levels. We consider price- and warranty-dependent demand, price- and age-dependent return, and age-dependent remanufacturing cost in the model development. Both linear and non-linear forms of these functions are investigated. First, under some restrictive conditions of upgrade level and age distribution of received cores, special cases of the problem, which can be solved using a recently developed non-linear optimisation solver, are presented. We also implement a particle swarm optimisation algorithm for the solution of the original problem when all the restrictive assumptions are dropped. Finally, numerical experiments and sensitivity analysis are presented to address different aspects of the model and the solution approaches.
Acknowledgements
The authors would like to thank the associate editor and two anonymous referees for their valuable comments and suggestions which improved the earlier versions of this paper.
Additional information
Notes on contributors
Seyed Ahmad Yazdian
Seyed Ahmad Yazdian is a PhD candidate in the Department of Industrial Engineering at Iran University of Science and Technology, Tehran, Iran. His research interests include applied operations research, remanufacturing planning, warranty analysis and supply chain management.
Kamran Shahanaghi
Kamran Shahanaghi is an assistant professor of industrial engineering at Iran University of Science and Technology, Tehran, Iran. His research interests include maintenance and reliability, multiple criteria decision-making, uncertain programming and operations research. He has published papers in journals such as Computers and Industrial Engineering, Expert Systems with Applications, Applied Mathematical Modelling, Engineering Failure Analysis and RAIRO Operations Research among others.
Ahmad Makui
Ahmad Makui is an associate professor of industrial engineering at Iran University of Science and Technology, Tehran, Iran. He received his BS degree in industrial engineering in 1985, an MS in industrial engineering in 1991 and a PhD in industrial engineering (operations research) in 2000. His research interests include production planning, supply chain, decision-making techniques and mathematical modelling. He has authored papers published in JORS, EJOR, IJAMT, JOMS and some other journals and conferences.