Accelerating ant colony optimization by using local search
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015.
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| Формат: | Дисертація |
| Мова: | English |
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BRAC University
2015
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| Онлайн доступ: | http://hdl.handle.net/10361/4369 |
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10361-43692022-01-26T10:08:22Z Accelerating ant colony optimization by using local search Tabassum, Nabila Haque, Maruful Showkat, Dilruba Department of Computer Science and Engineering, BRAC University Computer science and engineering Ant colony optimization This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015. Cataloged from PDF version of thesis report. Includes bibliographical references (page 42-45). Optimization is very important fact in terms of taking decision in mathematics, statistics, computer science and real life problem solving or decision making application. Many different optimization techniques have been developed for solving such functional problem. In order to solving various problem computer Science introduce evolutionary optimization algorithm and their hybrid. In recent years, test functions are using to validate new optimization algorithms and to compare the performance with other existing algorithm. There are many Single Object Optimization algorithm proposed earlier. For example: ACO, PSO, ABC. ACO is a popular optimization technique for solving hard combination mathematical optimization problem. In this paper, we run ACO upon five benchmark function and modified the parameter of ACO in order to perform SBX crossover and polynomial mutation. The proposed algorithm SBXACO is tested upon some benchmark function under both static and dynamic to evaluate performances. We choose wide range of benchmark function and compare results with existing DE and its hybrid DEahcSPX from other literature are also presented here. Nabila Tabassum Maruful Haque B. Computer Science and Engineering 2015-09-03T06:19:17Z 2015-09-03T06:19:17Z 2015 2015-08 Thesis ID 11301006 ID 11201003 http://hdl.handle.net/10361/4369 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 45 pages application/pdf BRAC University |
| institution |
Brac University |
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Institutional Repository |
| language |
English |
| topic |
Computer science and engineering Ant colony optimization |
| spellingShingle |
Computer science and engineering Ant colony optimization Tabassum, Nabila Haque, Maruful Accelerating ant colony optimization by using local search |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015. |
| author2 |
Showkat, Dilruba |
| author_facet |
Showkat, Dilruba Tabassum, Nabila Haque, Maruful |
| format |
Thesis |
| author |
Tabassum, Nabila Haque, Maruful |
| author_sort |
Tabassum, Nabila |
| title |
Accelerating ant colony optimization by using local search |
| title_short |
Accelerating ant colony optimization by using local search |
| title_full |
Accelerating ant colony optimization by using local search |
| title_fullStr |
Accelerating ant colony optimization by using local search |
| title_full_unstemmed |
Accelerating ant colony optimization by using local search |
| title_sort |
accelerating ant colony optimization by using local search |
| publisher |
BRAC University |
| publishDate |
2015 |
| url |
http://hdl.handle.net/10361/4369 |
| work_keys_str_mv |
AT tabassumnabila acceleratingantcolonyoptimizationbyusinglocalsearch AT haquemaruful acceleratingantcolonyoptimizationbyusinglocalsearch |
| _version_ |
1814307455982632960 |