Multi-Objective Intelligent Vehicle Routing Optimization by Dynamic Complex Neutrosophic Particle Swarm

Abstract

The multi-objective scheduling optimization problem is one of the important research problems in intelligent vehicle scheduling systems. For scheduling optimization problem of seafood intelligent vehicles, a scheduling optimization model based on the Dynamic complex Neutrosophic Particle Swarm (DNPS) is proposed. Experimental comparison with traditional genetic and immune was conducted, and the experimental data showed that the average distance was shortened by 1.15km, the average waiting time was shortened by 56s in the process of seafood intelligent vehicle scheduling. It can effectively ensure the freshness problem of seafood and improve the quality of delivery service.