Green logistics optimization model for forward and reverse logistics using genetic algorithm

Green logistics has been receiving much attention due to more focus mainly on environmental protection and conservation, green legislations, customer´s increased awareness for clean environment, and sustainability and this drives to more importance given to environmental conservation and protection practices like recycle, reprocess, reuse and emission control to minimize economic cost and environmental effects. The reverse logistics is a key constituent of green logistics. Reverse logistics deal with the collection re-usable packaging and end of life goods for recycling or remanufacturing. The present research is encouraged by the practice oxygen delivery to the hospitals in a predefined time window. Here a genetic algorithm is applied in proposed logistics optimization model for generating routes of two models of VRP for simultaneous pickup and delivery with time window and two pick up strategies full pickups and partial pickups. Then routes are selected after comparison based on a set of economic and environmental cost factors. The experimental results show that the total cost is lower for full pickup strategy.