Traditionally, process planning and scheduling were executed sequentially. Sequential execution of process planning and scheduling has numerous shortcomings including unbalanced resource utilization and unrealistic process plans.
Recently, researchers have investigated various approaches to overcome the shortcoming of the sequential approach for process planning and scheduling. Although there are various meta-heuristics for IPPS, they still need further improvements using a more efficient algorithm. Moreover, there is a lack of research of effective algorithms for multi-objective IPPS.
Kim Yong Ho, an institute head at the Faculty of Automatics, proposed a new multi-objective differential evolutionary algorithm combined with chaotic map to solve IPPS problems.
The experimental results showed that the proposed algorithm is better than other multi-objective optimization algorithms for IPPS problems.
For further details, you can refer to his paper “A Chaotic-Based Multi-Objective Differential Evolutionary Algorithms for Integrated Process Planning and Scheduling” in “Proceedings of KUTIC-2025”.