Bi-Objective Optimization for Multi-Row Facility Layout Problem Integrating Automated Guided Vehicle Path

For machining workshops that use automated guided vehicles (AGVs) for material handling and management, workstation layout and AGV path are coupling factors affecting the material handling cost (MHC). The multi-row layout is a typical pattern in many machining workshops, and currently, there is a lack of studies on the multi-row layout problem (MRLP) while taking into account the AGV path. This study established a bi-objective multi-row layout optimization methodology integrating the AGV path to minimize MHC and area occupancy. Specifically, workstations and transfer stations were arranged in the workshop following several non-intersecting AGV paths to decrease the material handling distance between workstations. First, a multi-row layout optimization model was established. Second, a hybrid approach combining the non-dominated sorting genetic algorithm-II (NSGA-II) and tabu search (TS) was proposed to solve it. The effectiveness of the proposed model was verified in the practice of a structural components machining workshop, and the results were compared with that of a loop-based layout. In addition, the proposed approach was compared with an exact approach and another hybrid approach based on a genetic algorithm (GA) and simulated annealing (SA). The experimental results showed that the proposed approach was able to achieve better sets of Pareto solutions within reasonable computational time.