A free-slack-based genetic algorithm for the robotic cell problem with controllable processing times

Abstract

We present a novel genetic algorithm for the Robotic Cell Problem with controllable processing times. This challenging problem arises in an automated production cell that consists of m consecutive machines as well as a material handling robot. The problem requires finding the operations processing times, job assignment, and robot movements. The objective is to minimize the makespan subject to a budget constraint. We describe a free-slack-based genetic algorithm for the linear resource consumption case. We present the results of a computational study and we provide evidence that the proposed algorithm consistently outperforms MIP-based heuristics from the literature. Springer International Publishing Switzerland 2016.