Beyond optimality: Genetic Algorithms and Fuzzy Inference for Coil-Order allocation in the steel industry.

The paper addresses the Coil-Order Allocation problem in steel industry via Genetic Algorithms through two approaches: a basic solution with a standard objective function and an advanced method incorporating a Fuzzy Inference System to mimic human decision-making. Both solutions were tested on real-world data from a tinplate production plant, achieving significant improvements in orders fulfillment and material utilization compared to manual allocation. The basic genetic approach outperforms the baseline in efficiency, while the fuzzy-genetic method demonstrate flexibility for complex, customizable optimization. The results show the potential of combining heuristic techniques and fuzzy logic to enhance industrial operations.