GA for large-scale bus evacuation problems

GA for large-scale bus evacuation problems with the objective of minimizing the evacuation time

For GA, the typical chromosome representation and crossover operation are inspired by Bederina and Hifi (2018). The chromosome represents a complete plan for all the buses, which is constructed by a group of genes, and the number of genes is equal to the number of available buses. Each gene points to a list of trips, which corresponds to the complete route schedule for the respective bus. Each trip is represented as a pair (p, s), where p corresponds to the pickup point, and s is the shelter point. As the depot of each bus is given, the travel from the depot to the first pickup point can be inferred from the gene. Similar to that described in Bederina and Hifi (2018), the crossover operation exchanges the best gene of the two selected parents, and the conflicting trips are then modified from the original genes. In this study, the best gene of a chromosome is denoted as the plan of a bus whose travel time is closest to the average travel time of this chromosome. In mutation operation, a group of trips (more than two) are randomly shuffled.