Algoritma Ant Colony Optimization pada Quadratic Assignment Problem
Quadratic Assignment Problem (QAP) is one extension of the assignment problem by setting n facilities to n certain locations to minimize the total assignment costs. QAP is also a combinatorial optimization problem that is a problem that has a finite set of solutions. Basically the solution of combin...
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| Format: | Article |
| Language: | English |
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Department of Mathematics, Universitas Negeri Gorontalo
2019-07-01
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| Series: | Jambura Journal of Mathematics |
| Subjects: | |
| Online Access: | https://ejurnal.ung.ac.id/index.php/jjom/article/view/2353 |
| _version_ | 1828349037831520256 |
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| author | Oni Soesanto Pardi Affandi Nurul Dasima Astuti |
| author_facet | Oni Soesanto Pardi Affandi Nurul Dasima Astuti |
| author_sort | Oni Soesanto |
| collection | DOAJ |
| description | Quadratic Assignment Problem (QAP) is one extension of the assignment problem by setting n facilities to n certain locations to minimize the total assignment costs. QAP is also a combinatorial optimization problem that is a problem that has a finite set of solutions. Basically the solution of combinatorial problems can be obtained with the right results but for complex problems with larger data sizes it is quite difficult to calculate because the time used is long enough for the completion process. One of the algorithms implemented in the completion of QAP is the Ant Colony Optimization (ACO) algorithm is an algorithm that mimics the behavior of ants in finding food from the nest to a food source with the help of indirect communication called pheromone, so that pheromone is used to find optimal solutions with quite a short time. in this research ACO is used to solve the QAP problem by using a random proportional of rule formula then getting the smallest solution and renewing the pheromone until the assignment is stable and the solution obtained is fixed until the maximum assignment solution. The results obtained to complete the Quadratic Assignment Problem with the Ant Colony Optimization algorithm to get a solution to the QAP problems tested in the Nugent case resulted in a more minimal solution and the placement of appropriate location facilities through pheromone assistance and stored in a taboo list so that all facilities get a decent location with a worth it short time in completion. |
| first_indexed | 2024-04-14T01:04:48Z |
| format | Article |
| id | doaj.art-c739a36f830c4cec9648e42d2b01d087 |
| institution | Directory Open Access Journal |
| issn | 2654-5616 2656-1344 |
| language | English |
| last_indexed | 2024-04-14T01:04:48Z |
| publishDate | 2019-07-01 |
| publisher | Department of Mathematics, Universitas Negeri Gorontalo |
| record_format | Article |
| series | Jambura Journal of Mathematics |
| spelling | doaj.art-c739a36f830c4cec9648e42d2b01d0872022-12-22T02:21:18ZengDepartment of Mathematics, Universitas Negeri GorontaloJambura Journal of Mathematics2654-56162656-13442019-07-011210411010.34312/jjom.v1i2.23531720Algoritma Ant Colony Optimization pada Quadratic Assignment ProblemOni Soesanto0Pardi Affandi1Nurul Dasima Astuti2Program Studi Matematika, Fakultas MIPA Universitas Lambung MangkuratProgram Studi Matematika, Fakultas MIPA Universitas Lambung MangkuratProgram Studi Matematika, Fakultas MIPA Universitas Lambung MangkuratQuadratic Assignment Problem (QAP) is one extension of the assignment problem by setting n facilities to n certain locations to minimize the total assignment costs. QAP is also a combinatorial optimization problem that is a problem that has a finite set of solutions. Basically the solution of combinatorial problems can be obtained with the right results but for complex problems with larger data sizes it is quite difficult to calculate because the time used is long enough for the completion process. One of the algorithms implemented in the completion of QAP is the Ant Colony Optimization (ACO) algorithm is an algorithm that mimics the behavior of ants in finding food from the nest to a food source with the help of indirect communication called pheromone, so that pheromone is used to find optimal solutions with quite a short time. in this research ACO is used to solve the QAP problem by using a random proportional of rule formula then getting the smallest solution and renewing the pheromone until the assignment is stable and the solution obtained is fixed until the maximum assignment solution. The results obtained to complete the Quadratic Assignment Problem with the Ant Colony Optimization algorithm to get a solution to the QAP problems tested in the Nugent case resulted in a more minimal solution and the placement of appropriate location facilities through pheromone assistance and stored in a taboo list so that all facilities get a decent location with a worth it short time in completion.https://ejurnal.ung.ac.id/index.php/jjom/article/view/2353quadratic assignment problemant colony optimizationtabu listpheromone |
| spellingShingle | Oni Soesanto Pardi Affandi Nurul Dasima Astuti Algoritma Ant Colony Optimization pada Quadratic Assignment Problem Jambura Journal of Mathematics quadratic assignment problem ant colony optimization tabu list pheromone |
| title | Algoritma Ant Colony Optimization pada Quadratic Assignment Problem |
| title_full | Algoritma Ant Colony Optimization pada Quadratic Assignment Problem |
| title_fullStr | Algoritma Ant Colony Optimization pada Quadratic Assignment Problem |
| title_full_unstemmed | Algoritma Ant Colony Optimization pada Quadratic Assignment Problem |
| title_short | Algoritma Ant Colony Optimization pada Quadratic Assignment Problem |
| title_sort | algoritma ant colony optimization pada quadratic assignment problem |
| topic | quadratic assignment problem ant colony optimization tabu list pheromone |
| url | https://ejurnal.ung.ac.id/index.php/jjom/article/view/2353 |
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