Capacitated disassembly scheduling with random demand and operation time. Issue 6 (3rd June 2022)

• Record Type: Journal Article
• Authors: Zhou, Fuli; He, Yandong; Ma, Panpan; Lim, Ming K.; Pratap, Saurabh
• Is Part Of: Journal of the Operational Research Society. Volume 73:Issue 6(2022)
• Page Start: 1362
• Page End: 1378
• Publication Date: 2022-06-03
• Subjects: Capacitated disassembly scheduling -- random demand and operation time -- disassembly yield -- fixed sample size (FSS) sampling strategy -- HGA; Operations research -- Periodicals; 658.4034
• DOI: 10.1080/01605682.2021.1911603
• Languages: English
• ISSNs: 0160-5682

Abstract

Abstract: The disassembly activity, regarding as the crucial stage in recycling operations, has attracted increasing focus owing to the significance of eco-economics and environmental issues. This paper examines the capacitated disassembly scheduling with demand and disassembly operation time uncertainty consideration, which is the problem of determining the quantity of the end-of-life (EOL) products (root item) to be disassembled while satisfying recycling market. The addressed problem is formulated as a novel stochastic programming model and a hybrid genetic-based algorithm (HGA) is proposed to derive the best solution. To deal with the uncertain demand of disassembled parts/modules (leaf item) and the disassembly operation time, the fixed sample size (FSS) sampling strategy is employed and embedded into the designed heuristic algorithm, lunched by the Monte Carlo Simulation. The numerical instances under different scales are performed, and results show that the developed HGA manifests good performance in terms of accuracy and efficiency.