Intelligent travel route planning for bridge crane type of material handling equipment in cellular manufacturing

In this work, we propose the bridge crane travel path optimization for batch order picking (BOP). Successful solving this problem is valuable to many application areas in manufacturing systems. We then investigate the feasibility of using ant colony optimization (ACO) meta-heuristics to address the proposed problem. Simulation tests are executed separately based on two ACO algorithms. Finally, the bridge crane operating performance measure index is employed to evaluate the experimental results achieved by different ACO algorithms. Experimental case study demonstrates the effectiveness and applicability of the selected ACO approaches to our proposed BOP problem for bridge crane.