Optimization of Vehicle Routing Problem Based on Multi-Objective Genetic Algorithm

Ru Zhong; Jian Ping Wu; Yi Man Du

doi:10.4028/www.scientific.net/AMM.253-255.1356

Paper Titles

The Study of Traffic Simulation System Based on B/S Pattern
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A Short-Term Combination Forecasting Model for Traffic Flow Based on the BP Neural Network
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Study of Travel Mode Choice Behavior Based on Nested Logit Model
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Lane-Based Road Network Model and its Application in Simulation Road Network Modeling
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Optimization of Vehicle Routing Problem Based on Multi-Objective Genetic Algorithm
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Research of Vehicle Scheduling Problem and Algorithm Based on Emergency Needs
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Research on the Traffic Simulation Platform Based on the Real-Time Mobile Phone Data
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Study on Multi-Depot Vehicle Routing Problem Based on Cloud Adaptive Particle Swarm Optimization
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Model Reference Adaptive Algorithm Designed for Automatic Train Braking Control
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Optimization of Vehicle Routing Problem Based on Multi-Objective Genetic Algorithm

Abstract:

When there are multiple objectives co-existent in Vehicle routing problem(VRP), it is difficult to achieve optical status simultaneously. To solve this issue, it introduces a method of improved multi-objective Genetic Algorithm (MOGA). It adopts an approach close to heuristic algorithm to cultivate partial viable chromosomes, route decoding to ensure that all individuals meet constraints and uses relatively efficient method of arena contest to construct non-dominated set. Finally programme to fulfill the multi-objective algorithm and then apply it in the standard example of VRP to verity its effectiveness by comparison with the existing optimal results.