A Real-Time Double Flexible Job Shop Scheduling Problem Under Industry 5.0

In today's Industry 5.0 environment, there is a strong emphasis on human considerations, sustainability, and resilience. These key factors have significant implications for production environments, and accurately representing them becomes crucial. In this article, we investigate a real-time double flexible job shop scheduling problem (DyDFJSP) with consideration of human factors fatigue and energy consumption. We propose a dynamic strategy based on an enhanced genetic algorithm (EGA) to solve the problem. The proposed algorithm is subjected to a comprehensive experimental analysis on a dynamic scenario, thoroughly examining its effectiveness in solving the DyDFJSP and providing a solid proof of concept for its applicability.