.png){kind=icon}
返回
Dominance-based multiobjective simulated annealing
.png){kind=icon}
OA
AI
DOI：10.1109/TEVC.2007.904345.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
code-division multiple-access (CDMA) networks
dominance
multiple objectives
simulated annealing
期刊
IF:
12
论文数:
1.9K
被引数:
2.4W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏Printable cellulose-based electroconductive composites for sensing elements in paper electronics
OAAI
OAAI分享收藏
查看更多内容