JOURNAL ARTICLE

A SIMULATED ANNEALING ALGORITHM FOR MULTIOBJECTIVE OPTIMIZATION

A SuppapitnarmKeith A. SeffenGeoffrey T. ParksP. John Clarkson

Year: 2000 Journal:   Engineering Optimization Vol: 33 (1)Pages: 59-85   Publisher: Taylor & Francis

Abstract

Abstract This paper describes a novel implementation of the Simulated Annealing algorithm designed to explore the trade-off between multiple objectives in optimization problems. During search, the algorithm maintains and updates an archive of non-dominated solutions between each of the competing objectives. At the end of search, the final archive corresponds to a number of optimal solutions from which the designer may choose a particular configuration. A new acceptance probability formulation based on an annealing schedule with multiple temperatures (one for each objective) is proposed along with a novel restart strategy. The performance of the algorithm is demonstrated on three examples. It is concluded that the proposed algorithm offers an effective and easily implemented method for exploring the trade-off in multiobjective optimization problems. Keywords: Simulated annealingmultiobjective optimizationengineering design Additional informationNotes on contributorsG. T. PARKS Corresponding author, e-mail: [email protected]

Keywords:
Simulated annealing Mathematical optimization Computer science Schedule Multi-objective optimization Adaptive simulated annealing Optimization algorithm Algorithm Mathematics

Metrics

251
Cited By
3.08
FWCI (Field Weighted Citation Impact)
20
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Multi-Objective Optimization Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Optimization and Mathematical Programming
Physical Sciences →  Engineering →  Control and Systems Engineering
Optimal Experimental Design Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research

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