Multi-objective Memetic Algorithm for Solving Pickup and Delivery Problem with Dynamic Customer Requests and Traffic Information

This paper formulates one-to-many-to-one pickup and delivery problems with dynamic customer requests and traffic information. A multi-objective memetic algorithm namely prioLSH-MOMA is proposed to solve the problems. The new algorithm is characterized with a priority and locality-sensitive hashing based local search. prioLSH-MOMA is designed to find an optimal route of a dynamic pickup and delivery problem in terms of route length and workload. Particularly, a re-planning strategy is introduced to handle the dynamic information. Priority and locality-sensitive hashing based local search is applied to line tune the candidate routes during the evolution process. prioLSH-MOMA is evaluated with two dynamic pickup and delivery problems simulated on real-world maps and the results demonstrate the efficiency of the proposed algorithm.