By Topic

An investigation of the use of local search in NP-hard problems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Newth, D. ; Sch. of Environ. & Inf. Sci., Charles Sturt Univ., Albury, NSW, Australia ; Kirley, M. ; Green, D.G.

We combine local search algorithms with genetic algorithms. In this context local search can be thought of as learning over an individual's lifetime. We investigate two different ways of incorporating learning into the hybrid algorithm: Lamarckian evolution and the Baldwin effect. For each model we systematically vary the proportion of the population undergoing learning. We found that the quality of solution improves significantly at or above a critical level of learning

Published in:

Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE  (Volume:4 )

Date of Conference:

2000