Operator-probability adaptation in a genetic-algorithm/heuristic hybrid for optical network wavelength allocation

Mark Sinclair

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Operator-probability adaptation, in a genetic-algorithm/heuristic hybrid for minimum cost routing and wavelength allocation of multi-wavelength all-optical transport networks is described. The hybrid algorithm uses an object-oriented representation of networks, and incorporates four operators: path mutation, single-point crossover, reroute and shift-out. The adaptation algorithm is based on that by Davis, but uses simplified operator accounting. Experimental results from three fifteen-node test networks, obtained using a tool for optical network optimisation, modelling and design (NOMaD), illustrate the interesting dynamic behaviour of the adaptation algorithm. They suggest that, in this application, with powerful problem-specific operators, the main benefits of operator-probability adaptation are in relieving the experimenter of the burden of setting initial probabilities and in the early performance of the hybrid, rather than in improvements of the final solution quality obtained.
Original languageEnglish
Title of host publication1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360)
DOIs
Publication statusPublished - May 1998

Fingerprint

Dive into the research topics of 'Operator-probability adaptation in a genetic-algorithm/heuristic hybrid for optical network wavelength allocation'. Together they form a unique fingerprint.

Cite this