Abstract
Green supply chain management is based on performing environmental management into supply chain network in order to decrease the environmental side effects in the product life cycle. So, in this paper, a bi-objective nonlinear programming for an integrated forward/reverse logistics network with the aim of increasing total profit of the network and maximizing the score of green design and quality indicators and green scrap score is discussed. Quality and green design indicators are considered for the forward network and the green scrap score are defined for scrapped products collected and disassembled in the reverse network. The mentioned network includes three echelons in the forward flow (production centers (factories), distribution centers, and customer zones) and three echelons in the reverse flow (collection/disassembly centers, recycling centers, and disposal centers). The main contribution of this study is to consider green design indicators and quality indicators for developing final products. Furthermore, in the model of this research, some constraints are regarded to determine the amount of paper and plastic consumption in the packaging of the products. After presenting the considered model, Multi-objective Particle Swarm Optimization and Non-dominated Sorting Genetic (NSGA-II) meta-heuristic Algorithms are proposed to find a set of Pareto-optimal solutions. Then, their output is compared through some samples with different sizes to prove their workability.
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Porkar, S., Mahdavi, I., Maleki Vishkaei, B. et al. Green supply chain flow analysis with multi-attribute demand in a multi-period product development environment. Oper Res Int J 20, 1405–1435 (2020). https://doi.org/10.1007/s12351-018-0382-5
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DOI: https://doi.org/10.1007/s12351-018-0382-5