dc.contributor.author | Smith, Kevin I. | en_GB |
dc.contributor.author | Everson, Richard M. | en_GB |
dc.contributor.author | Fieldsend, Jonathan E. | en_GB |
dc.contributor.author | Murphy, Chris | en_GB |
dc.contributor.author | Misra, Rashmi | en_GB |
dc.date.accessioned | 2013-03-05T16:12:22Z | en_GB |
dc.date.accessioned | 2013-03-20T12:10:37Z | |
dc.date.accessioned | 2014-07-24T14:40:10Z | |
dc.date.issued | 2008-05-28 | en_GB |
dc.description.abstract | Simulated annealing is a provably convergent optimizer for single-objective problems. Previously proposed multiobjective extensions have mostly taken the form of a single-objective simulated annealer optimizing a composite function of the objectives. We propose a multiobjective simulated annealer utilizing the relative dominance of a solution as the system energy for optimization, eliminating problems associated with composite objective functions. We also propose a method for choosing perturbation scalings promoting search both towards and across the Pareto front. We illustrate the simulated annealer's performance on a suite of standard test problems and provide comparisons with another multiobjective simulated annealer and the NSGA-II genetic algorithm. The new simulated annealer is shown to promote rapid convergence to the true Pareto front with a good coverage of solutions across it comparing favorably with the other algorithms. An application of the simulated annealer to an industrial problem, the optimization of a code-division-multiple access (CDMA) mobile telecommunications network's air interface, is presented and the simulated annealer is shown to generate nondominated solutions with an even and dense coverage that outperforms single objective genetic algorithm optimizers. | en_GB |
dc.identifier.citation | Vol. 12 (3), pp. 323 - 342 | en_GB |
dc.identifier.doi | 10.1109/TEVC.2007.904345 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/15260 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.relation.replaces | http://hdl.handle.net/10036/4419 | |
dc.relation.replaces | 10036/4419 | |
dc.subject | Pareto optimisation | en_GB |
dc.subject | code division multiple access | en_GB |
dc.subject | genetic algorithms | en_GB |
dc.subject | mobile radio | en_GB |
dc.subject | simulated annealing | en_GB |
dc.subject | CDMA mobile telecommunications network | en_GB |
dc.subject | Pareto front | en_GB |
dc.subject | dominance-based multiobjective simulated annealing | en_GB |
dc.subject | genetic algorithm | en_GB |
dc.subject | Code-division multiple-access (CDMA) networks | en_GB |
dc.subject | dominance | en_GB |
dc.subject | multiple objectives | en_GB |
dc.title | Dominance-Based Multiobjective Simulated Annealing | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2013-03-05T16:12:22Z | en_GB |
dc.date.available | 2013-03-20T12:10:37Z | |
dc.date.available | 2014-07-24T14:40:10Z | |
dc.identifier.issn | 1089-778X | en_GB |
dc.description | Copyright © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_GB |
dc.identifier.journal | IEEE Transactions on Evolutionary Computation | en_GB |