Optimizing Last Mile Delivery Using Public Transport with Multi-Agent Based Control

The majority of research work carried out in the field of Operations Research have relied on optimization algorithms to improve the pick-up and delivery problem. Most studies aim to solve the vehicle routing problem, to accommodate optimum delivery orders, vehicles etc. This paper focuses on developing a system model, which uses existing Public Transport facility of a city for the transportation of small and medium sized packaged goods, to avoid further aggravating the situation of urban congestion and also help reduce green house gas emissions. The research carried out investigates the feasibility of the proposed multi-agent based simulation model, for efficiency of cost, time and energy consumption. The Dijkstra Shortest Path algorithm and Nested Monte Carlo Search have been implemented to build a time based cost matrix which is used to generate a tour plan for intermodal delivery of goods. The quality of the tour is dependent on the efficiency of the search algorithm implemented for plan generation and route planning. The results reveal a definite advantage of using Public Transportation over existing delivery approaches in terms of energy efficiency.