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|Title:||Performance Comparison of Jumping Gene Adaptations of the Elitist Non-dominated Sorting Genetic Algorithm|
|Keywords:||Elitist nondominated sorting genetic algorithm|
|Source:||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. https://doi.org/10.1002/9781118341704.ch4|
|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.|
|Source Title:||Multi-Objective Optimization in Chemical Engineering: Developments and Applications|
|Appears in Collections:||Staff Publications|
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