Abstract
The incorporation of reverse logistics into production routing problems can promote and coordinate the implementation of sustainable development for supply chains. This study aims to incorporate reverse logistics into production routing problems and investigate the reduction of carbon emissions under carbon cap-and-trade. Mixed-integer programming models are proposed for the production routing problem with reverse logistics by considering simultaneous pickups and deliveries in vehicle routing subproblems. To solve this problem, we propose a solution method of a branch-and-cut guided search algorithm based on adaptation of known valid inequalities. Computational results highlight the trade-offs among various performance indicators, including emission levels and operational costs of production, inventory holding, fuel consumption, and drivers.
Highlights
In the promotion and coordination of sustainable development for supply chains, environmental concerns about production and logistic activities have greatly increased in recent years
Since integrated operations can help achieve the goal of reduced environmental harm while remaining operational effectiveness [1], supply chain optimization problems such as the production routing problem (PRP) that aim at optimal joint decisions of production, inventory, distribution, and routing, have recently received a considerable attention [2]
We model PRPSPD under the carbon cap-and-trade regulatory mechanism by integrating the pollution routing model and the pollution lot-sizing model
Summary
In the promotion and coordination of sustainable development for supply chains, environmental concerns about production and logistic activities have greatly increased in recent years. Since integrated operations can help achieve the goal of reduced environmental harm while remaining operational effectiveness [1], supply chain optimization problems such as the production routing problem (PRP) that aim at optimal joint decisions of production, inventory, distribution, and routing, have recently received a considerable attention [2]. Besides integrating operations forward, closed-loop supply chain optimization exhibited a reduction in environmental impact [5]. Return flow processes in a closed-loop supply chain usually consist of: (1) product collection from consumers; (2) reverse logistics to take collected products back; (3) screening, assorting, and disposal to specify the most economically attractive reuse alternatives; (4) remanufacturing; and (5) remarketing to produce and utilize new markets [6]. The PRP can be extended naturally to involve reverse logistics
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