Analysis and comparison of DABC and ACO in a scheduling problem

Abstract

The present study consists in the comparison of two metaheuristics in a scheduling problem (SP), in particular in the minimization of the makespan in flowshop problem. The two selected metaheuristics were DABC (Discrete Artificial Bee Colony) and ACO (Ant Colony Optimization). For the performance analysis, the metaheuristics were tuned with an extensive DOE study, subsequently, several tests were performed. Thirty-one evenly distributed instances were generated for a in-depth analysis and each one was subjected to three runs for each metaheuristic. Through the results obtained, it was possible to concluded that the DABC has a better performance when compared to SA and ACO. SA and ACO have a similar performance in the chosen problem. These conclusions were supported by descriptive statistics and statistical inference.