Multi-objective vehicle routing problem with flexible scheduling for the collection of refillable glass bottles: A case study

Abstract

• Optimization of the collection of refillable glass bottles. • A multi-objective mathematical model based on a VRP with additional considerations. • A decision making tool with indicators to analyze the quality of the solution. • The production of several real data sets inspired by real-life application. Deposit return systems have started making their reappearance as more environmentally conscious consumers seek ways to effectively reduce their carbon footprint. An example is the management of refillable glass bottles which requires a well-organized collection network with inventory management. A collection planning with an efficient algorithm and information system has to be applied. This paper investigates, using integer linear programming, a vehicle routing problem with time constraints to provide flexibility as well as priority rules to avoid inventory saturation at collection points. The model presented, based on a real-life application in the city of Lyon and surrounding areas, includes several objectives with specific assumptions. The result of the optimization is a vehicle routing plan with flexible scheduling based on time slots. Numerical experiments are conducted on instances of different scales making it possible to model the current problem as well as its future evolution. These experiments consider several instances, using a single vehicle among three vehicle types (cargo-bicycle, car and van) and a network composed of 20 stores/clients to collect bottles from. The results show the impacts of the priority rules on the solution obtained and additional indicators are proposed in order to analyze more precisely the quality of the solution in terms of financial cost and environmental impact. The proposed model and program will help make appropriate decisions in planning and scheduling the routes of the vehicles for the refillable glass bottle collection, especially in urban areas.