Abstract
Green supply chain is among the hottest recent research subjects in supply chain management which not only optimises the costs and service levels during a time period all over the chain, but also considers effect of emission of CO2 greenhouse gas on the overall value of supply chain for sustainable development. Therefore, in this paper, a bi-objective, multi-stage, multi-product quadratic optimisation model is proposed by taking into account the quality level of the purchased materials plus their reprocessing extra costs to a system in stochastic mode and the environmental costs of CO2 emission. Here we also consider both straight and step by step transportation in supply chain network design. Since the problem is NP-hard, a priority-based genetic algorithm model is proposed. In this paper, three methods including BOM, LP-metric and elastic BOM are applied to solve small data, whereas, elastic BOM offers larger solution space and more justified solutions. Hence, for solving large data, three priority-based genetic algorithms corresponding to MODM techniques are utilised. Then, by using TOPSIS for small and ANOVA for medium and large problems, the optimum procedure for balancing the existing costs and CO2 emission in the chain is selected.
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