A Family Competition Genetic Algorithm for the Pickup and Delivery Problems with Time Window

This paper presents a new approach based on genetic algorithms to solving the singlevehicle pickup and delivery problem with time window constraints (1-PDPTW). In particular, we illustrate how the Family Competition Genetic Algoritm (FCGA) is applied to the 1-PDPTW, and compare its results with previous solutions to the problem. Genetic algorithms have been shown to find feasible or near-optimal solutions when traditional methods would fail within a reasonble amount of time. By incorporating the concept of families to maintain diversity, FCGA further improves solution quality and increases the probability of finding the optimal solutions without much extra resource demands. Extensive experiments on FCGA with various crossover and mutation operators show that the new approach succeeds in finding the optimal solutions for 1-PDPTW under 50 tasks, and can obtain near-optimal or feasible solutions in most problems up to 100 tasks.