Ant Colony Optimization for Workforce Planning with Hybridization

Abstract

Production organization plays a key role in the success of any enterprise. Optimizing workforce planning can improve the overall organization of production. The main goal is to minimize the assignment cost of the workers who will perform the planned work. The problem is known to be NPhard, therefore we will apply methods from the field of artificial intelligence. For this reason, most of the existing methods hardly find feasible solutions. We propose Ant Colony Optimization Algorithm with hybridization, combination with local search procedures. We compare and analyze their performance.