Solving Battalion Rescheduling Problem Using Multi-objective Genetic Algorithms

In this paper, we consider the problem of rescheduling human resources in a battalion where new activities are assigned to the battalion by higher headquarters, requiring modification of an existing original schedule. The problem is modeled as a multi-criteria optimization problem with three objectives: (i) maximizing the number of tasks that are performed, (ii) minimizing the number of high-priority tasks that are missed, and (iii) minimizing the differences between the original schedule and the modified one. In order to solve the optimization model, we adopt Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The accuracy of NSGA-II in this context is verified by considering a small-sized problem where it is easy to verify solutions. Furthermore, we consider a realistic problem instance for a battalion with 400 agents and 66 tasks in the initial schedule. We present the computational results of rescheduling when unpredictable activities emerge.