Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow

Abstract

Emergency supplies scheduling needs to consider the state of the demanders, and reasonably scheduling and resource allocation are the heart of efficient rescue. Taking rescue time, scheduling cost and demanders’ satisfaction as goals, in this paper, an emergency supplies scheduling model based on multi-objective optimization was proposed to provide a wealth of decision-making information. Then four multi-objective optimization algorithms are employed to obtain the optimal set of scheduling models. In addition, we design the minimum time cost model and the shortest route cost model by considering the change of the road network status. The extensive simulation experiments are conducted on a real urban traffic dataset. The experimental results show that the two cost models can serve different scheduling needs and provide efficient scheduling for emergency supplies.

Keywords

• Logistics scheduling
• MOP
• Swarm intelligence algorithms
• Spatio-temporal trajectory
• Traffic flow