Modelling and Solving the Inventory Routing Problem with CO2 Emissions Consideration and Transshipment Option

This paper introduces a multi-period, multi-product green inventory routing problem with transshipment option, where capacitated vehicles distribute products from multiple suppliers to one customer to meet the given demand of products. The demand associated with the customer is assumed to be time-varying and deterministic. Greenhouse gas emissions from transport activities in a supply chain are a main reason for global warming. One of the main types of greenhouse gas is CO2 from vehicles and its impact on the environment. Inventory and routing decisions can help in the reduction of CO2 emissions if these emissions are taken into account by researchers. Also, as one of the main topics of this paper, the transshipment option is considered in the proposed model. The model is a mixed-integer programming (MIP) which has been solved and validated by General Algebraic Modeling System (GAMS). Finally, small and large-scale test problems are randomly generated and solved by the simulated annealing algorithm (SA). The computational results for different test problems showed that the proposed SA performs well and converges fast to reasonable solutions compared with GAMS. According to the results, it is determined that the transshipment option reduces CO2 emissions and costs by shortening the distance traveled.

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