Matheuristic for Multi Vehicles Green Inventory Routing Problem with product substitution by considering customer satisfaction

About the Project

This project aims to develop matheuristic algorithm which combines mathematical programming and metaheuristic methods to solve bi-objective of multi vehicles green inventory routing problem with one way product substitution by considering customer satisfaction (MVGIRP-PS). There is a fleet of heterogeneous vehicles to transport the products from each supplier to meet the demand of the assembly plant over the planning finite horizon. In the real world there are possibilities that the demand of customers cannot meet on time due to the limitation of various aspects from the company such as production capacity, vehicle capacity and economical aspects. Therefore, in this research we are taking into account the one-way product substitution, i.e., high-quality product may be used to meet the demand for the low-quality product to prevent the stock-out. Greenhouse gases (GHG) emission has become one of the major concerns globally as they are key players in global warming. One of the GHG is carbon dioxide which mainly causes global warming as increasing the concentration of carbon dioxide in the atmosphere will trap the heat and cause the Earth’s surface to become warmer. Therefore, the first objective of this research which not only considers the inventory, substitution, and transportation cost but also considers the fuel consumption and emission cost. Meanwhile, the second objective is to take into account the customers’ satisfaction by minimizing different aspects to reduce the stock-out.

Main Supervisor: Dr Lily Wong, Monash University