Automated Planning and Scheduling with Swarm Intelligence

Automated planning and scheduling aims to design intelligent algorithms that could allocate resources for solving a given planning and scheduling problem and meet specific purposes. The current status of swarm intelligence on planning and scheduling tasks is discussed and the challenges of swarm intelligence and automated planning algorithms design are analyzed in this paper. Interpretability is the foundation of understanding problems' properties and algorithms' search behaviors. The interpretability of algorithms is discussed from interpretable processes and interpretable results. Based on the interpretability analysis, swarm intelligence's evolution and learning ability could design the automated algorithm.