یک الگوریتم برنامه ریزی نرم افزاری چند منظوره برای الگوریتم تولید ریخته گری عملیات فولادسازی مستمر با الگوبرداری

Uncertainty is the most challenging problem for implementing scheduling algorithms under practical environments, since the schedule released into a shop floor with optimal objectives often deteriorates or even suffers infeasibility during its execution period. This paper focuses on the uncertain scheduling problem arising from the steelmaking-continuous casting (SCC) manufacturing system and proposes a multi-objective soft scheduling (MOSS) to overcome this challenge. In this study, a soft-form schedule including critical decisions and characteristic indicators is introduced to provide more flexibility against random disturbances. In the MOSS algorithm, we propose a preference-inspired chemical reaction optimization (PICRO) algorithm to solve the uncertain SCC scheduling problem with soft-form solutions, in which the objectives of waiting time, cast-break and over-waiting are tackled by the preference-inspired method. In the PICRO, a simulation-based T-test method is used to evaluate solutions, and a knowledge-based local search (KLS) is embedded to enhance the convergence of PICRO. Following this, a clean-up procedure is proposed for ranking and selecting the best solutions in the final population output by the PICRO. Computational experiments on the synthetic and real-world SCC scheduling instances demonstrate that the proposed MOSS algorithm can result in significantly better solutions compared to other algorithms under practical environments.