Title :
GIDEON: a genetic algorithm system for vehicle routing with time windows
Author :
Thangiah, Sam R. ; Nygard, Kendall E. ; Juell, Paul L.
Author_Institution :
Dept. of Comput. Sci., North Dakota State Univ., Fargo, ND, USA
Abstract :
Addresses the vehicle routing problem with time windows (VRPTW). The VRPTW involves routing a fleet of vehicles, of limited capacity and travel time, from a central depot to a set of geographically dispersed customers with known demands within specified time windows. The authors describe GIDEON, a genetic algorithm system to heuristically solve the VRPTW. GIDEON consists of two distinct modules: a global clustering module that assigns customers to vehicles by a process called genetic sectoring (GENSECT) and a local route optimization module (SWITCH-OPT). On a standard set of 56 VRPTW problems obtained from the literature, GIDEON did better than the alternate methods on 41 of them, with an average reduction of 3.9% in fleet size and 4.4% in distance traveled for the 56 problems. GIDEON took an average of 127 CPU seconds to solve a problem on the Solbourne 5/802 computer
Keywords :
distributive data processing; genetic algorithms; heuristic programming; transportation; 127 s; GENSECT; GIDEON; SWITCH-OPT; Solbourne 5/802 computer; central depot; fleet size; genetic algorithm system; genetic sectoring; geographically dispersed customers; global clustering module; heuristic solution; local route optimization module; time windows; travel time; vehicle routing; Artificial intelligence; Computer science; Costs; Decision making; Dynamic scheduling; Genetic algorithms; Job shop scheduling; Operations research; Routing; Vehicle dynamics;
Conference_Titel :
Artificial Intelligence Applications, 1991. Proceedings., Seventh IEEE Conference on
Conference_Location :
Miami Beach, FL
Print_ISBN :
0-8186-2135-4
DOI :
10.1109/CAIA.1991.120888
