Crew Operation Scheduling Using Simulated Evolution Method

Abstract

Since a crew operation scheduling problem is a large-scale combinatorial problem, only human experts can make schedule with trial and error in a long time by hand. Some mathematical approaches have been proposed to find optimum solution with expending huge time, but no effective approach has been presented to find constraint satisfaction solution in a short time for real world problems. We propose a new method for crew operation scheduling using simulated evolution. This method enables (1) making a crew operation scheduling by non-experts, (2) high-speed search of a feasible solution, (3) interactiveness for system and a user, (4) evaluate resource management. Users can make a high quality schedule for crew operations and take decision supports for resource management. This method can find feasible solutions in several minutes for middle scale real world problems that needs several days by human experts.