Affiliation:
1. Université de Technologie Belfort – Montbéliard, France
2. Wuhan University of Technology, China
Abstract
The Vehicle Routing Problem (VRP) is one of important combinatorial problems, which holds a central place in logistics management. One of the most widely studied problems in the VRP family is the Multi-Depot Vehicle Routing Problem (MDVRP), where more than one depot is considered. In this chapter, the authors focus on a new extension of the MDVRP in which goods loaded by the vehicle are restricted due to limited stocks available at warehouses. More specifically, this extension consists in determining a least cost routing plan that can satisfy all the customs demands by delivering available stocks. Indeed, this problem is often encountered when goods are shortage in some warehouses. To deal with the problem efficiently, a memetic algorithm is proposed in this chapter. The authors study this approach on a set of modified benchmark instances and compare its performance to a pure genetic algorithm.
Reference74 articles.
1. An evolutionary framework using particle swarm optimization for classification method PROAFTN
2. A robust predictive model for base shear of steel frame structures using a hybrid genetic programming and simulated annealing method
3. Purposeful model parameters genesis in simple genetic algorithms
4. Modified simple genetic algorithms improving convergence time for the purposes of fermentation process parameter identification.;M.Angelova;WSEAS Transactions on Systems,2012
5. Evolutionary artificial neural network for selecting flexible manufacturing systems under disparate level-of-satisfaction of decision maker.;A.Bhattacharya;International Journal of Innovative Computing, Information, & Control,2007
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献