Multi-heuristic desirability ant colony system heuristic for non-permutation flowshop scheduling problems

摘要

Ant colony optimization (ACO) is a novel intelligent meta-heuristic originating from the foraging behavior of ants. An efficient heuristic of ACO is the ant colony system (ACS). This study presents a multi-heuristic desirability ACS heuristic for the non-permutation flow-shop scheduling problem, and verifies the effectiveness of the proposed heuristic by performing computational experiments on a well-known non-permutation flowshop benchmark problem set. Over three-quarters of the solutions to these experiments are superior to the current best solutions in relevant literature. Since the proposed heuristic is comprehensible and effective, this study successfully explores the excellent potential of ACO for solving non-permutation flowshop scheduling problems.