Hybrid Genetic Algorithm for Designing Logistics Network, VRP and AGV Problems

The use of hybrid genetic algorithm (Hybrid GA) in the networks design has been growing the last decades due to the fact that many practical networks design problems are NP hard. This paper examines recent developments in the field of evolutionary optimization for network design. We combine the various hybrid genetic algorithms to a wide range of practical network problems such as a logistics network model, VRP (Vehicle Routing Problem), and AGV (Automated Guided Vehicles) dispatching problem. It is covered as follows: first, we apply the hybrid priority-based GA for solving fixed-charge Transportation Problem (fcTP), which the proposed approach is more effective in larger size than benchmark test problems. Second, we give the several resent GA approach for solving Multistage Logistic Network Problem. Third, we introduce Vehicle Routing Problem (VRP) and variants of VRP. We apply the priGA for solving Multi-depot vehicle routing problem with time windows (mdVRP-tw). Lastly, we apply a priority-based based GA to solve an automated guided vehicles (AGV) dispatching problem in Flexible Manufacturing System (FMS).