Time Dependent Green VRP for Cold Chain Logistics

To reduce the environmental Pollution emissions caused by market activities, cold chain logistics companies also considered the emission of harmful gases for better service in satisfying customers’ demands. In the cold supply chain, goods are supplied and distributed that become corrupt and degraded over time. Therefore, to keep such goods fresh, the temperature must be constantly and continuously controlled, which in turn requires more fuel consumption. Also, in vehicle routing problem, the travel time of a route and fuel consumption does not only depend on the distance traveled, but also on the speed and time of day when that route is traveled. In this study, a new mixed-integer optimization model of the vehicle routing problem in a cold supply chain concerning congestion is presented with the aim is to minimize costs of Pollution emissions. In this model, in addition to the cost of the environmental Pollution emissions, other costs are considered, including the vehicle operating cost, transportation, loss of quality, product freshness, and penalty cost for arriving outside the customer's time window. In continuing, a solution method based on Benders decomposition is applied to solve the proposed model for large size networks. The computational results showed that the presented model provides the optimal route and travel time of the vehicle by considering the reduction of pollution and the appropriate speed. Also, the implementation of the solution algorithm on several test instances with different sizes showed the efficiency of the algorithm in reducing the solution time and obtaining a good solution.