A dynamic screening algorithm for multiple objective simulated annealing optimization

被引：0

作者：

Marcoulaki, Eftychia C. ^{[1
]}

Papazoglou, Ioannis A. ^{[1
]}

机构：

[1] Natl Ctr Sci Res Demokritos, Syst Reliabil & Ind Safety Lab, Athens 15310, Greece

来源：

20TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING | 2010年 / 28卷

关键词：

multiple objective optimization; simulated annealing; redundancy apportionment problem; MULTIOBJECTIVE OPTIMIZATION; COMBINATORIAL OPTIMIZATION;

D O I：

暂无

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

This work proposes new multiple objective optimization (MOO) technology, using a Monte Carlo-based algorithm stemmed from simulated annealing (SA). Since the expected result in MOO tasks is usually a set of Pareto-optimal solutions, the optimization problem states assumed here are themselves sets of solutions. The stochastic search follows a series of reversible state transitions at constant probability, to enjoy convergence properties of stationary Markov processes. The proposed technology is tested against the optimal design of a process system involving equipment placed in a serial/parallel arrangement, with three optimization objectives: the system cost, reliability and weight.

引用

页码：349 / 354

页数：6

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