Feasibility preserving constraint-handling strategies for real parameter evolutionary optimization
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| Argitaratua izan da: | Computational Optimization and Applications vol. 62, no. 3 (Dec 2015), p. 851 |
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| Beste egile batzuk: | , |
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Springer Nature B.V.
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| Sarrera elektronikoa: | Citation/Abstract Full Text Full Text - PDF |
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| 024 | 7 | |a 10.1007/s10589-015-9752-6 |2 doi | |
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| 045 | 2 | |b d20151201 |b d20151231 | |
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| 100 | 1 | |a Padhye, Nikhil | |
| 245 | 1 | |a Feasibility preserving constraint-handling strategies for real parameter evolutionary optimization | |
| 260 | |b Springer Nature B.V. |c Dec 2015 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a (ProQuest: ... denotes formulae and/or non-USASCII text omitted; see image) Evolutionary algorithms (EAs) are being routinely applied for a variety of optimization tasks, and real-parameter optimization in the presence of constraints is one such important area. During constrained optimization EAs often create solutions that fall outside the feasible region; hence a viable constraint-handling strategy is needed. This paper focuses on the class of constraint-handling strategies that repair infeasible solutions by bringing them back into the search space and explicitly preserve feasibility of the solutions. Several existing constraint-handling strategies are studied, and two new single parameter constraint-handling methodologies based on parent-centric and inverse parabolic probability (IP) distribution are proposed. The existing and newly proposed constraint-handling methods are first studied with PSO, DE, GAs, and simulation results on four scalable test-problems under different location settings of the optimum are presented. The newly proposed constraint-handling methods exhibit robustness in terms of performance and also succeed on search spaces comprising up-to ...... variables while locating the optimum within an error of ....... The working principle of the IP based methods is also demonstrated on (i) some generic constrained optimization problems, and (ii) a classic 'Weld' problem from structural design and mechanics. The successful performance of the proposed methods clearly exhibits their efficacy as a generic constrained-handling strategy for a wide range of applications. | |
| 653 | |a Optimization | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Differential scanning calorimetry | ||
| 653 | |a Computer science | ||
| 653 | |a Analysis | ||
| 653 | |a Studies | ||
| 653 | |a Variables | ||
| 653 | |a Computer engineering | ||
| 653 | |a Linear programming | ||
| 653 | |a Methods | ||
| 653 | |a Values | ||
| 653 | |a Mutation | ||
| 653 | |a Feasibility | ||
| 700 | 1 | |a Mittal, Pulkit | |
| 700 | 1 | |a Deb, Kalyanmoy | |
| 773 | 0 | |t Computational Optimization and Applications |g vol. 62, no. 3 (Dec 2015), p. 851 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1734964545/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/1734964545/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1734964545/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |