Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/55932
Title: Evolutionary multi-objective optimization of substation maintenance using Markov model
Authors: Chang, C.S. 
Yang, F.
Keywords: Dynamic Markov model
Minimum cut sets
Multi-objective evolutionary algorithms
Pareto front
Issue Date: Jun-2007
Source: Chang, C.S.,Yang, F. (2007-06). Evolutionary multi-objective optimization of substation maintenance using Markov model. Engineering Intelligent Systems 15 (2) : 75-81. ScholarBank@NUS Repository.
Abstract: Improving the reliability and reducing the overall cost are two important but often conflicting objectives for substations. Proper scheduling of preventive maintenance provides an effective means to tradeoff between the two objectives. In this paper, Pareto-based multi-objective evolutionary algorithms are proposed to optimize the maintenance activities because of their abilities of robust search towards best-compromise solutions for large-size optimization problems. Markov model is proposed to predict the deterioration process, maintenance operations, and availability of individual components. Minimum cut sets method is employed to identify the critical components by evaluating the overall reliability of interconnected systems. Pareto-fronts are generated for comparisons with other substation configurations. Results for four different substation configurations are presented to demonstrate potentials of the proposed approach for handling more complicated configurations. © 2007 CRL Publishing Ltd.
Source Title: Engineering Intelligent Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/55932
ISSN: 14728915
Appears in Collections:Staff Publications

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