A robust bi-objective programming approach to environmental closed-loop supply chain network design under uncertainty
Zahra Homayouni and
Mir Saman Pishvaee
International Journal of Mathematics in Operational Research, 2020, vol. 16, issue 2, 257-278
Abstract:
Imposition of strict environmental protection acts and the imperative need of the best possible allocation of resources have given birth to the concept of low carbon logistics. Environmental laws force the manufacturers to extend their existing supply chains to form a closed-loop supply chain (CLSC) through the setup of an efficient recovery system. In this paper, a multi-objective robust optimisation model is proposed for the design of CLSC network under uncertainty. First, a deterministic bi-objective mixed integer linear programming (BOMILP) model is developed for designing a CLSC network. Then, the robust counterpart of the proposed BOMILP is presented to cope with the real-world uncertainty. The first objective aims to maximise the total profit generated in the CLSC network and the second objective minimises the environmental pollution of the CLSC network. The proposed bi-objective model is solved using a multi-choice goal programming (MCGP) approach.
Keywords: closed-loop supply chain; CLSC; multi-choice goal programming; MCGP; environmental issues; robust optimisation. (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmore:v:16:y:2020:i:2:p:257-278
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