Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices
In agile software processes, the issue of team size is an important one. In this work we look at how to find the optimal, or near optimal, self-organizing team size using a genetic algorithm (GA) which considers team communication efforts. Communication, authority, roles, and learning are the team’s...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2018-12-01
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| Series: | Journal of Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jisys-2018-0085 |
| _version_ | 1819121734658293760 |
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| author | Almadhoun Wael Hamdan Mohammad |
| author_facet | Almadhoun Wael Hamdan Mohammad |
| author_sort | Almadhoun Wael |
| collection | DOAJ |
| description | In agile software processes, the issue of team size is an important one. In this work we look at how to find the optimal, or near optimal, self-organizing team size using a genetic algorithm (GA) which considers team communication efforts. Communication, authority, roles, and learning are the team’s performance characteristics. The GA has been developed according to performance characteristics. A survey was used to evaluate the communication weight factors, which were qualitatively assessed and used in the algorithm’s objective function. The GA experiments were performed in different stages: each stage results were tested and compared with the previous results. The results show that self-organizing teams of sizes ranged from five to nine members scored more. The model can be improved by adding other team characteristics, i.e. software development efforts and costs. |
| first_indexed | 2024-12-22T06:41:16Z |
| format | Article |
| id | doaj.art-07e656135a8c421b877b8a5b60bd7749 |
| institution | Directory Open Access Journal |
| issn | 0334-1860 2191-026X |
| language | English |
| last_indexed | 2024-12-22T06:41:16Z |
| publishDate | 2018-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Intelligent Systems |
| spelling | doaj.art-07e656135a8c421b877b8a5b60bd77492022-12-21T18:35:25ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2018-12-012911151116510.1515/jisys-2018-0085Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile PracticesAlmadhoun Wael0Hamdan Mohammad1Department of Engineering, ADNOC Offshore, Abu Dhabi, United Arab EmiratesSchool of Mathematical and Computer Sciences, Heriot-Watt University, Dubai, United Arab Emirates, e-mail: hamdan@yu.edu.joIn agile software processes, the issue of team size is an important one. In this work we look at how to find the optimal, or near optimal, self-organizing team size using a genetic algorithm (GA) which considers team communication efforts. Communication, authority, roles, and learning are the team’s performance characteristics. The GA has been developed according to performance characteristics. A survey was used to evaluate the communication weight factors, which were qualitatively assessed and used in the algorithm’s objective function. The GA experiments were performed in different stages: each stage results were tested and compared with the previous results. The results show that self-organizing teams of sizes ranged from five to nine members scored more. The model can be improved by adding other team characteristics, i.e. software development efforts and costs.https://doi.org/10.1515/jisys-2018-0085agilegenetic algorithmoptimizationteam size68t04 |
| spellingShingle | Almadhoun Wael Hamdan Mohammad Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices Journal of Intelligent Systems agile genetic algorithm optimization team size 68t04 |
| title | Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices |
| title_full | Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices |
| title_fullStr | Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices |
| title_full_unstemmed | Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices |
| title_short | Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices |
| title_sort | optimizing the self organizing team size using a genetic algorithm in agile practices |
| topic | agile genetic algorithm optimization team size 68t04 |
| url | https://doi.org/10.1515/jisys-2018-0085 |
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