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https://doi.org/10.1002/9781118341704.ch4
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dc.title | Performance Comparison of Jumping Gene Adaptations of the Elitist Non-dominated Sorting Genetic Algorithm | |
dc.contributor.author | Sharma, S. | |
dc.contributor.author | Nabavi, S.R. | |
dc.contributor.author | Rangaiah, G.P. | |
dc.date.accessioned | 2014-06-18T05:33:28Z | |
dc.date.available | 2014-06-18T05:33:28Z | |
dc.date.issued | 2013-04-02 | |
dc.identifier.citation | Sharma, S.,Nabavi, S.R.,Rangaiah, G.P. (2013-04-02). Performance Comparison of Jumping Gene Adaptations of the Elitist Non-dominated Sorting Genetic Algorithm. Multi-Objective Optimization in Chemical Engineering: Developments and Applications : 103-127. ScholarBank@NUS Repository. <a href="https://doi.org/10.1002/9781118341704.ch4" target="_blank">https://doi.org/10.1002/9781118341704.ch4</a> | |
dc.identifier.isbn | 9781118341667 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/68013 | |
dc.description.abstract | Industrial problems are complex in nature, and often have multiple performance criteria. The elitist nondominated sorting genetic algorithm (NSGA-II) has been used to optimize many process design and operation problems for two or more objectives. In order to improve the performance of this algorithm, the jumping-gene concept from natural genetics has been incorporated in NSGA-II. Several jumping-gene adaptations have been proposed and used to solve mathematical and application problems in different studies. In this chapter, four jumping-gene adaptations are selected and comprehensively evaluated on a number of two-objective unconstrained and constrained test functions. Three quality metrics, namely, generational distance, spread and inverse generational distance are employed to evaluate the distribution and convergence of the obtained Pareto-optimal solutions at the final generation and also at selected intermediate generations. Additionally, a search termination criterion based on the improvement in the Pareto-optimal front, has been described and used to check convergence of NGSA-II with the selected jumping gene adaptations. © 2013 John Wiley & Sons, Ltd. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/9781118341704.ch4 | |
dc.source | Scopus | |
dc.subject | Elitist nondominated sorting genetic algorithm | |
dc.subject | Jumping-gene adaptations | |
dc.subject | Multi-objective optimization | |
dc.type | Others | |
dc.contributor.department | CHEMICAL & BIOMOLECULAR ENGINEERING | |
dc.description.doi | 10.1002/9781118341704.ch4 | |
dc.description.sourcetitle | Multi-Objective Optimization in Chemical Engineering: Developments and Applications | |
dc.description.page | 103-127 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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