Workshop Scheduling that Integrates NSGA-II and CSA

Addressing the simultaneous scheduling of tasks and Automated Guide Vehicle (AGV) in flexible workshop systems. Consider maximizing utilization with limited resources to save costs as much as possible. Constructed to minimize the maximum machine duration, the consumption time of a single handling robot, and the total transport time of all handling robots as a function of the objective. Design an improved algorithm (INGCSA) that combines NGSA-II (Non-dominated Sorting Genetic Algorithms) and Clonal Selection Algorithm (CSA) to solve such problems. First, the population is layered by nondominated ordering; secondly, cloning of superior and medium populations; Finally, different mutation probabilities are adopted for different levels of population, which effectively retains excellent individuals and prevents the algorithm from falling into local optimum. The simulation results show that the algorithm has good optimization ability, short running time and high stability.