A novel multiobjective lognormal-beta differential evolution approach for the transformer design optimization. Issue 2 (16th April 2018)
- Record Type:
- Journal Article
- Title:
- A novel multiobjective lognormal-beta differential evolution approach for the transformer design optimization. Issue 2 (16th April 2018)
- Main Title:
- A novel multiobjective lognormal-beta differential evolution approach for the transformer design optimization
- Authors:
- Tsili, Marina
Amoiralis, Eleftherios I.
Leite, Jean Vianei
Moreno, Sinvaldo R.
Coelho, Leandro dos Santos - Abstract:
- Abstract : Purpose: Real-world applications in engineering and other fields usually involve simultaneous optimization of multiple objectives, which are generally non-commensurable and conflicting with each other. This paper aims to treat the transformer design optimization (TDO) as a multiobjective problem (MOP), to minimize the manufacturing cost and the total owing cost, taking into consideration design constraints. Design/methodology/approach: To deal with this optimization problem, a new method is proposed that combines the unrestricted population-size evolutionary multiobjective optimization algorithm (UPS-EMOA) with differential evolution, also applying lognormal distribution for tuning the scale factor and the beta distribution to adjust the crossover rate (UPS-DELFBC). The proposed UPS-DELFBC is useful to maintain the adequate diversity in the population and avoid the premature convergence during the generational cycle. Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria. Findings: Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria. Originality/value: This paper develops a promising UPS-DELFBC approach to solve MOPs. The TDO problems for three different transformer specifications, with 160, 400 and 630 kVA, have been addressed in this paper.Abstract : Purpose: Real-world applications in engineering and other fields usually involve simultaneous optimization of multiple objectives, which are generally non-commensurable and conflicting with each other. This paper aims to treat the transformer design optimization (TDO) as a multiobjective problem (MOP), to minimize the manufacturing cost and the total owing cost, taking into consideration design constraints. Design/methodology/approach: To deal with this optimization problem, a new method is proposed that combines the unrestricted population-size evolutionary multiobjective optimization algorithm (UPS-EMOA) with differential evolution, also applying lognormal distribution for tuning the scale factor and the beta distribution to adjust the crossover rate (UPS-DELFBC). The proposed UPS-DELFBC is useful to maintain the adequate diversity in the population and avoid the premature convergence during the generational cycle. Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria. Findings: Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria. Originality/value: This paper develops a promising UPS-DELFBC approach to solve MOPs. The TDO problems for three different transformer specifications, with 160, 400 and 630 kVA, have been addressed in this paper. Optimization results show the potential and efficiency of the UPS-DELFBC to solve multiobjective TDO and to produce multiple Pareto solutions. … (more)
- Is Part Of:
- Engineering computations. Volume 35:Issue 2(2018)
- Journal:
- Engineering computations
- Issue:
- Volume 35:Issue 2(2018)
- Issue Display:
- Volume 35, Issue 2 (2018)
- Year:
- 2018
- Volume:
- 35
- Issue:
- 2
- Issue Sort Value:
- 2018-0035-0002-0000
- Page Start:
- 955
- Page End:
- 978
- Publication Date:
- 2018-04-16
- Subjects:
- Multiobjective optimization -- Evolutionary algorithms -- Differential evolution -- Electrical power systems -- Transformer design optimization
Computer-aided engineering -- Periodicals
Computer graphics -- Periodicals
620.00285 - Journal URLs:
- http://info.emeraldinsight.com/products/journals/journals.htm?id=ec ↗
http://www.emeraldinsight.com/journals.htm?issn=0264-4401 ↗
http://www.emeraldinsight.com/0264-4401.htm ↗
http://www.emeraldinsight.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1108/EC-01-2017-0024 ↗
- Languages:
- English
- ISSNs:
- 0264-4401
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3758.580800
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