Tabu search and genetic algorithm in rims production process assignment.

The article focuses on optimizing the assignment and scheduling of production resources in the manufacturing process of car rims, specifically addressing the allocation of rim machining operations to production stations. It extends the classical assignment problem by incorporating operation times, changeover durations, and machine capacities, and applies heuristic algorithms—Genetic Algorithm and Tabu Search—to solve the complex scheduling challenges faced by an automotive company producing over 1000 rim types on 45 casting and 18 machining machines. Computational experiments demonstrate that these heuristic methods improve machine utilization and reduce the longest working time compared to the company’s manual scheduling, enabling more efficient production planning and potentially reducing costs. The study concludes that automatic scheduling using these algorithms can effectively replace manual planning in complex manufacturing environments and suggests future research on applying heuristic methods to other production areas.