Paper Info
Title
A fast and effective insertion algorithm for multi-depot vehicle routing problem with fixed distribution of vehicles and a new simulated annealing approach
Abstract
Multi-depot Vehicle Routing Problem has great practical value to the logistics and supply chain management. The fixed distribution of vehicles variant (MDVRPFD) brings it one step closer to the practical use. Based on the simple fact that all sub-routes of an optimal route must be optimal, a new randomized best insertion (RBI) algorithm is proposed. The proposed insertion algorithm is highly effective in minimizing number of vehicles and fast. Compared to the best known result published for MDVRPFD variant, the solutions generated by this new insertion algorihtm require 20% fewer vehicles. Adopting a generalized n-op neighborhood operator, a Simulated Annealing approach yields a reduction of 12% in total distance compared to best known results of MDVRPFD. Areas: meta-heuristic, vehicle routing, industrial applications of AI.
Year
DOI
Venue
2006
10.1007/11779568_32
IEA/AIE
Keywords
Field
DocType
practical use,new randomized best insertion,proposed insertion algorithm,known result,new insertion,multi-depot vehicle routing problem,new simulated annealing approach,multi-depot vehicle,great practical value,effective insertion algorithm,vehicles variant,optimal route,mdvrpfd variant,fixed distribution,supply chain management,simulated annealing,vehicle routing
Simulated annealing,Randomized algorithm,Mathematical optimization,Vehicle routing problem,Computer science,Meta heuristic,Algorithm,Supply chain management,Operator (computer programming)
Conference
Volume
ISSN
ISBN
4031
0302-9743
3-540-35453-0
Citations 
PageRank 
References 
3
0.39
6
Authors
2
Name
Order
Citations
PageRank
Andrew Lim1172.44
Wenbin Zhu221415.34