Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions
The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swa...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/510763 |
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| author | Kian Sheng Lim Zuwairie Ibrahim Salinda Buyamin Anita Ahmad Faradila Naim Kamarul Hawari Ghazali Norrima Mokhtar |
| author_facet | Kian Sheng Lim Zuwairie Ibrahim Salinda Buyamin Anita Ahmad Faradila Naim Kamarul Hawari Ghazali Norrima Mokhtar |
| author_sort | Kian Sheng Lim |
| collection | DOAJ |
| description | The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm. |
| format | Article |
| id | doaj-art-def7edaf8cfb4ec48c92889a3871a693 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-def7edaf8cfb4ec48c92889a3871a6932025-02-03T05:54:05ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/510763510763Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated SolutionsKian Sheng Lim0Zuwairie Ibrahim1Salinda Buyamin2Anita Ahmad3Faradila Naim4Kamarul Hawari Ghazali5Norrima Mokhtar6Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, MalaysiaFaculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, 26600 Pekan, MalaysiaFaculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, MalaysiaFaculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, MalaysiaFaculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, 26600 Pekan, MalaysiaFaculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, 26600 Pekan, MalaysiaDepartment of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, MalaysiaThe Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.http://dx.doi.org/10.1155/2013/510763 |
| spellingShingle | Kian Sheng Lim Zuwairie Ibrahim Salinda Buyamin Anita Ahmad Faradila Naim Kamarul Hawari Ghazali Norrima Mokhtar Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions The Scientific World Journal |
| title | Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions |
| title_full | Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions |
| title_fullStr | Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions |
| title_full_unstemmed | Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions |
| title_short | Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions |
| title_sort | improving vector evaluated particle swarm optimisation by incorporating nondominated solutions |
| url | http://dx.doi.org/10.1155/2013/510763 |
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