Green logistics decision support system for blood distribution in time window

Abstract

During previous years, the role of green logistics in the distribution management has seen a tremendous increase due to increased focus on environmental protection, consumer environmental concern, green legislation and sustainability. This has led to an increase in recycling, reuse and emission control to reduce economic and environmental costs. In this research, a genetic algorithm-based decision support system for the route generation and comparison of the routes based on various economic and environmental cost factors. A mixed integer linear programming formulation of four vehicle routing problems with simultaneous delivery and pickup (full and partial) and time window (hard and soft) is provided and solved by genetic algorithm. The real-life data of blood distribution is used for comparing VRPSDPTW variants on the basis of their economic and environmental value. The computational results indicate that total cost is lower in the case of a full pickup with the soft time windows. The logistic organisations can use the proposed system in decision making to select an appropriate transportation scheme with lower economic and environmental costs.