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A DSS Based on Multiple Criteria Decision Making for Maintenance Planning in an Electrical Power Distributor

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Evolutionary Multi-Criterion Optimization (EMO 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7811))

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Abstract

This paper presents a real world application that lead to the construction of a decision support system built to support maintenance planning in an electrical power distribution company. The outcome of the DSS is to determine the order of priority in which potential failure repair orders should be conducted. This company-specific problem has been structured and is similar to that of most electrical power distribution companies, since this company has a complex distribution network with different types of customers which leads it to considering different criteria such as income losses, the probability of service interruptions, national regulation criteria, and so forth. There is a specific budget for potential failure repair orders, while functional failure repairs are not modeled at this managerial level since once the service should not be interrupted and involves long term planning. During periodical inspections the entire distribution network is inspected and a database with all this data is maintained. Thereafter, the potential failures in the distribution network are converted into maintenance orders which typically amount to more than 4 times the annual sum allocated for potential failure repairs budget. After having structured the problem, a DSS was built to support maintenance planning that will result in an annual maintenance plan based on the company´s strategic criteria and national regulations.

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Almeida-Filho, A., Ferreira, R.J.P., Almeida, A. (2013). A DSS Based on Multiple Criteria Decision Making for Maintenance Planning in an Electrical Power Distributor. In: Purshouse, R.C., Fleming, P.J., Fonseca, C.M., Greco, S., Shaw, J. (eds) Evolutionary Multi-Criterion Optimization. EMO 2013. Lecture Notes in Computer Science, vol 7811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37140-0_58

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  • DOI: https://doi.org/10.1007/978-3-642-37140-0_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37139-4

  • Online ISBN: 978-3-642-37140-0

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