Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Optimization problem relates to finding the best solution from all feasible solutions. Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimi...
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2014
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| Online Access: | http://umpir.ump.edu.my/id/eprint/7319/ http://umpir.ump.edu.my/id/eprint/7319/1/IEEE_Exlpore_MySec_2014.pdf |
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ump-73192018-01-16T01:31:15Z http://umpir.ump.edu.my/id/eprint/7319/ Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions Mazlina, Abdul Majid Alsariera, Yazan A. Alamri, Hammoudeh S. Nasser, Abdullah M. Kamal Z., Zamli T Technology (General) Not Available Optimization problem relates to finding the best solution from all feasible solutions. Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. Owing to the fact that they are new and much of their relative performance are still unknown (as compared to other established meta-heuristic algorithms), Bacterial Foraging Optimization Algorithm (BFO) and Bat Algorithm (BA) have been adopted for comparison using the 12 selected benchmark functions. In order to ensure fair comparison, both BFO and BA are implemented using the same data structure and the same language and running in the same platform (i.e. Microsoft Visual C# with .Net Framework 4.5). We found that BFO gives more accurate solution as compared to BA (with the same number of iterations). However, BA exhibits faster convergence rate 2014 Conference or Workshop Item NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7319/1/IEEE_Exlpore_MySec_2014.pdf Mazlina, Abdul Majid and Alsariera, Yazan A. and Alamri, Hammoudeh S. and Nasser, Abdullah M. and Kamal Z., Zamli (2014) Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions. In: The 8th Malaysian Software Engineering Conference (MySEC 2014), 22-24 September 2014 , Resort World, Langkawi. . (Unpublished) |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Malaysia Pahang |
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UMP Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
T Technology (General) Not Available |
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T Technology (General) Not Available Mazlina, Abdul Majid Alsariera, Yazan A. Alamri, Hammoudeh S. Nasser, Abdullah M. Kamal Z., Zamli Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions |
| description |
Optimization problem relates to finding the best solution from all feasible solutions. Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. Owing to the fact that they are new and much of their relative performance are still unknown (as compared to other established meta-heuristic algorithms), Bacterial Foraging Optimization Algorithm (BFO) and Bat Algorithm (BA) have been adopted for comparison using the 12 selected benchmark functions. In order to ensure fair comparison, both BFO and BA are implemented using the same data structure and the same language and running in the same platform (i.e. Microsoft Visual C# with .Net Framework 4.5). We found that BFO gives more accurate solution as compared to BA (with the same number of iterations). However, BA exhibits faster convergence rate |
| format |
Conference or Workshop Item |
| author |
Mazlina, Abdul Majid Alsariera, Yazan A. Alamri, Hammoudeh S. Nasser, Abdullah M. Kamal Z., Zamli |
| author_facet |
Mazlina, Abdul Majid Alsariera, Yazan A. Alamri, Hammoudeh S. Nasser, Abdullah M. Kamal Z., Zamli |
| author_sort |
Mazlina, Abdul Majid |
| title |
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions |
| title_short |
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions |
| title_full |
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions |
| title_fullStr |
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions |
| title_full_unstemmed |
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions |
| title_sort |
comparative performance analysis of bat algorithm and bacterial foraging optimization algorithm using standard benchmark functions |
| publishDate |
2014 |
| url |
http://umpir.ump.edu.my/id/eprint/7319/ http://umpir.ump.edu.my/id/eprint/7319/1/IEEE_Exlpore_MySec_2014.pdf |
| first_indexed |
2023-09-18T22:03:56Z |
| last_indexed |
2023-09-18T22:03:56Z |
| _version_ |
1777414582392848384 |