A New GA Approach for the Vehicle Routing Problem

Authors:
Ang Juay Chin;Ho Wee Kit;Andrew Lim
Affiliations:
-;-;-
Venue:
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Year:
1999

Citing 5
Cited 4

GENITOR II.: a distributed genetic algorithm

Journal of Experimental & Theoretical Artificial Intelligence
Algorithms for the vehicle routing problems with time deadlines

American Journal of Mathematical and Management Sciences - Special issue: vehicle routing 2000: advances in time windows, optimality, fast bounds, & multi-depot routing
Introduction to genetic heuristics and vehicle routing problems with complex constraints

Advances in computational and stochastic optimization, logic programming, and heuristic search
Multiple Vehicle Routing with Time and Capacity Constraints Using Genetic Algorithms

Proceedings of the 5th International Conference on Genetic Algorithms
An Adaptive Clustering Method Using a Geometric Shape for Vehicle Routing Problems with Time Windows

Proceedings of the 6th International Conference on Genetic Algorithms

On the harmonious mating strategy through tabu search

Information Sciences: an International Journal - Special issue: Evolutionary computation
Memetic Algorithm Based on a Constraint Satisfaction Technique for VRPTW

ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Solving the truck and trailer routing problem based on a simulated annealing heuristic

Computers and Operations Research
Immunity-based hybrid evolutionary algorithm for multi-objective optimization in global container repositioning

Engineering Applications of Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper focuses on the study of a hybrid of two search heuristics, Tabu Search (TS) and Genetic Algorithm (GA) on Vehicle Routing Problem with Time-Windows (VRPTW). TS is a local search technique that has been successfully applied to many NP-complete problems. On the other hand, GA which is capable of searching multiple search areas in a search space is good in diversification. We shall investigate whether a hybrid of the two heuristic outperforms the individual heuristics alone.