Flexible Job Shop Scheduling Problem with Fuzzy Times and Due-Windows: Minimizing Weighted Tardiness and Earliness Using Genetic Algorithms

The current requirements of many manufacturing companies, such as the fashion, textile, and clothing industries, involve production multiple products with different processing routes short life cycles, which prevents obtaining deterministic setup times. Likewise, several industries present restrictions when changing from one reference to another in system, incurring variable sequence-dependent Therefore, this article aims solve flexible job shop scheduling problem (FJSSP) considering due windows, times, uncertainty A genetic algorithm is proposed FJSSP by integrating fuzzy logic minimize weighted penalties for tardiness/earliness. implemented a real-world case study fabric finishing it compared four heuristics adapted earliest date, critical reason, shortest time, Monte Carlo simulation. Results show that performance provides efficient satisfactory solutions concerning objective function computing time since overperforms (more than 30%) used benchmarks.