A multiobjective optimization of a UWB antenna using a self organizing genetic algorithm

2012 ◽  
Vol 54 (8) ◽  
pp. 1824-1828 ◽  
Author(s):  
C. R. M. Silva ◽  
H. W. C. Lins ◽  
S. R. Martins ◽  
E. L. F. Barreto ◽  
A. G. d'Assunção
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Uwb Antenna ◽  
Self Organizing

scholarly journals Multiobjective optimization design of the solar field and reverse osmosis system with preheating feed water using Genetic algorithm

2018 ◽  
Vol 6 (6) ◽  
pp. 624-642 ◽  
Author(s):  
Iman Ebrahimi Ghoujdi ◽  
Hasti Hadiannasab ◽  
Mokhtar Bidi ◽  
Abbas Naeimi ◽  
Mohammad Hossein Ahmadi ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Reverse Osmosis ◽  
Optimization Design ◽  
Feed Water ◽  
Solar Field

scholarly journals Optimizing the Self-Organizing Team Size Using a Genetic Algorithm in Agile Practices

2018 ◽  
Vol 29 (1) ◽  
pp. 1151-1165
Author(s):  
Wael Almadhoun ◽  
Mohammad Hamdan
Keyword(s):  
Genetic Algorithm ◽  
Software Development ◽  
Objective Function ◽  
The Self ◽  
Performance Characteristics ◽  
Team Size ◽  
Agile Practices ◽  
Team Characteristics ◽  
Agile Software ◽  
Self Organizing

Abstract 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.

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