Service-oriented bi-objective robust collection-disassembly problem with equipment selection

Abstract

The collection-disassembly problem plays an important role in a reverse supply chain. It coordinates the collection and disassembly activities for end-of-life (EOL) products. Most existing works consider the deterministic problems. However, in practice, demands of reusable components in EOL products may be uncertain. Besides, it is usually difficult to exactly obtain probability distributions of uncertain demands, due to inadequate historical data. This paper studies a collection-disassembly problem under partial known distributional information of component demands, in which equipments of the disassembly site, corresponding to different disassembly capacities, have to be selected. The objectives are to minimise the system cost and to maximise the customer service level. For the problem, a novel distributionally robust bi-objective formulation is proposed. Based on the Monte Carlo simulation and an ambiguity set, a sample average approximation (SAA) model and an approximated mixed integer programming (MIP) model are constructed, respectively. Then the two approximated formulations are solved, via the ε-constraint framework, and compared in numerical experiments.

Keywords:

• Reverse logistics
• disassembly planning
• collection of EOL products
• disassembly equipment selection
• robust optimisation
• multi-criteria decision making
• bi-objective optimisation

Disclosure statement

No potential conflict of interest was reported by the author(s).

ORCID

Alexandre Dolgui  http://orcid.org/0000-0003-0527-4716

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (NSFC) under grants 71432007,71531011,71571134,71771048,71832001,71871159. This work was also supported by the Fundamental Research Funds for the Central Universities.