Genetic algorithm based hybrid approach to solve uncertain multi-objective COTS selection problem for modular software system.
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| Title: | Genetic algorithm based hybrid approach to solve uncertain multi-objective COTS selection problem for modular software system. |
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| Authors: | Dhodiya, Jayesh M.1 (AUTHOR) jdhodiya2002@yahoo.com, Tailor, Anita Ravi1 (AUTHOR) |
| Source: | Journal of Intelligent & Fuzzy Systems. 2018, Vol. 34 Issue 4, p2103-2120. 18p. |
| Subjects: | Genetic algorithms, Modular programming, Membership functions (Fuzzy logic), Fuzzy logic, Parameter estimation |
| Abstract: | This paper presents a genetic algorithm (GA) based approach for solving a multi-objective credibilistic model (MOCM) for commercial-off-the-shelf (COTS) product selection problem subject to many realistic constraints by using an exponential membership function. To solve this problem, a fuzzy technique is utilized to handle each uncertain parameter by a credibility-based model and finds a different efficient solution by taking various shape parameters in the exponential membership function subject to all resource constraints and for each objective function, aspiration level is specified by the decision maker (DM). A real-world example is provided to represent the importance of the proposed approach with data set from the realistic situation. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Abstract: | This paper presents a genetic algorithm (GA) based approach for solving a multi-objective credibilistic model (MOCM) for commercial-off-the-shelf (COTS) product selection problem subject to many realistic constraints by using an exponential membership function. To solve this problem, a fuzzy technique is utilized to handle each uncertain parameter by a credibility-based model and finds a different efficient solution by taking various shape parameters in the exponential membership function subject to all resource constraints and for each objective function, aspiration level is specified by the decision maker (DM). A real-world example is provided to represent the importance of the proposed approach with data set from the realistic situation. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10641246 |
| DOI: | 10.3233/JIFS-162225 |
