The effects of initial population in genetic search for time constrained traveling salesman problems

Authors:
Cheng-Hong Yang;Kendall E. Nygard
Affiliations:
Department of Electronic Engineering, National Kaohsiung Institute of Technology, Kaohsiang, Taiwan;Department of Computer Science and Operations Research, North Dakota State University, Frago, North Dakota
Venue:
CSC '93 Proceedings of the 1993 ACM conference on Computer science
Year:
1993

Citing 4
Cited 0

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms for the Traveling Salesman Problem

Proceedings of the 1st International Conference on Genetic Algorithms
AllelesLociand the Traveling Salesman Problem

Proceedings of the 1st International Conference on Genetic Algorithms

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe the application of Genetic Algorithms to the traveling salesman problem with time windows. A new type of crossover operator, called edge-type crossover, with a heuristically selected initial population, is used in the genetic search. When compared with alternative methods from the literature, experiments indicate that the heuristic initialization speeds the genetic search process.