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A platform for research: civil engineering, architecture and urbanism
To increase revenue while being aware of environmental responsibility and uncertain demand, green forward–reverse logistics is an important part of research on supply chain management. This work seeks the optimal strategies for applying green forward–reverse logistics. A multi-product, multi-stage and multi-objective model is constructed of green forward–reverse logistics considering shortage costs and uncertain demand, which exist in reality. The aims of the proposed mathematical model are to maximize total revenue and minimize cost and environmental pollution. Two different sizes of forward–reverse logistics are discussed. The NSGA-II method is used to obtain the Pareto solutions of the mathematical model. The numerical results indicate that greater revenue can bring greater cost and environmental pollution in total. Considering the pollution problem, small firms have greater revenue-cost rates and lower cost-pollution rates. These results could help managers make more effective suggestions in production.
To increase revenue while being aware of environmental responsibility and uncertain demand, green forward–reverse logistics is an important part of research on supply chain management. This work seeks the optimal strategies for applying green forward–reverse logistics. A multi-product, multi-stage and multi-objective model is constructed of green forward–reverse logistics considering shortage costs and uncertain demand, which exist in reality. The aims of the proposed mathematical model are to maximize total revenue and minimize cost and environmental pollution. Two different sizes of forward–reverse logistics are discussed. The NSGA-II method is used to obtain the Pareto solutions of the mathematical model. The numerical results indicate that greater revenue can bring greater cost and environmental pollution in total. Considering the pollution problem, small firms have greater revenue-cost rates and lower cost-pollution rates. These results could help managers make more effective suggestions in production.
Analysing Green Forward–Reverse Logistics with NSGA-II
2020
Article (Journal)
Electronic Resource
Unknown
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