| Ant Colony Optimization (ACO), a constructive meta-heuristic optimization method, has been successfully applied to different optimization problems including TSP, QAP, VRP, etc. In order to further examine the robustness and versatility of the ACO algorithms three different classes of NP-hard single-objective problems, the Single Machine Total Weighted Tardiness problem (SMTWT), the Orienteering Problem (OP), and the Redundancy Allocation Problem (RAP), and a bi-objective version of the single machine problem, minimizing both total weighted tardiness (SMTWT) and total weighted number of tardy jobs (SMTWNTJ), are chosen as the focus of this research.; Well-known test problems from the literature are used and the results are compared with other published heuristics from the literature. The ACO algorithms are shown to be very competitive in terms of both computational effort and solution quality. This research is the first known application of the ACO algorithms to the OP, the RAP and the SMTWT and SMTWNTJ bi-criteria problem. A full characteristic study of each problem is given and these can be considered a good guide for those who want to address similar problems with ACO. |
