A tensor analysis improved genetic algorithm for online bin packing
Mutation in a Genetic Algorithm is the key variation operator adjusting the genetic diversity in a population throughout the evolutionary process. Often, a fixed mutation probability is used to perturb the value of a gene. In this study, we describe a novel data science approach to adaptively genera...
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| Format: | Conference or Workshop Item |
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2015
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| Online Access: | https://eprints.nottingham.ac.uk/33940/ |
| _version_ | 1848794738951454720 |
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| author | Asta, Shahriar Özcan, Ender |
| author_facet | Asta, Shahriar Özcan, Ender |
| author_sort | Asta, Shahriar |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Mutation in a Genetic Algorithm is the key variation operator adjusting the genetic diversity in a population throughout the evolutionary process. Often, a fixed mutation probability is used to perturb the value of a gene. In this study, we describe a novel data science approach to adaptively generate the mutation probability for each locus. The trail of high quality candidate solutions obtained during the search process is represented as a 3rd order tensor. Factorizing that tensor captures the common pattern between those solutions, identifying the degree of mutation which is likely to yield improvement at each locus. An online bin packing problem is used as an initial case study to investigate the proposed approach for generating locus dependent mutation probabilities. The empirical results show that the tensor approach improves the performance of a standard Genetic Algorithm on almost all classes of instances, significantly. |
| first_indexed | 2025-11-14T19:20:58Z |
| format | Conference or Workshop Item |
| id | nottingham-33940 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:20:58Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-339402020-05-04T17:13:21Z https://eprints.nottingham.ac.uk/33940/ A tensor analysis improved genetic algorithm for online bin packing Asta, Shahriar Özcan, Ender Mutation in a Genetic Algorithm is the key variation operator adjusting the genetic diversity in a population throughout the evolutionary process. Often, a fixed mutation probability is used to perturb the value of a gene. In this study, we describe a novel data science approach to adaptively generate the mutation probability for each locus. The trail of high quality candidate solutions obtained during the search process is represented as a 3rd order tensor. Factorizing that tensor captures the common pattern between those solutions, identifying the degree of mutation which is likely to yield improvement at each locus. An online bin packing problem is used as an initial case study to investigate the proposed approach for generating locus dependent mutation probabilities. The empirical results show that the tensor approach improves the performance of a standard Genetic Algorithm on almost all classes of instances, significantly. 2015-07-11 Conference or Workshop Item PeerReviewed Asta, Shahriar and Özcan, Ender (2015) A tensor analysis improved genetic algorithm for online bin packing. In: Genetic and Evolutionary Computation Conference (2015), 11-15 July 2015, Madrid, Spain. Genetic Algorithm Bin Packing Problem Tensor Genetic Diversity Fixation (Popular Genetics) Natural Selection Locus (Genetics) Mutation http://dl.acm.org/citation.cfm?doid=2739480.2754787 10.1145/2739480.2754787 10.1145/2739480.2754787 10.1145/2739480.2754787 |
| spellingShingle | Genetic Algorithm Bin Packing Problem Tensor Genetic Diversity Fixation (Popular Genetics) Natural Selection Locus (Genetics) Mutation Asta, Shahriar Özcan, Ender A tensor analysis improved genetic algorithm for online bin packing |
| title | A tensor analysis improved genetic algorithm for online bin packing |
| title_full | A tensor analysis improved genetic algorithm for online bin packing |
| title_fullStr | A tensor analysis improved genetic algorithm for online bin packing |
| title_full_unstemmed | A tensor analysis improved genetic algorithm for online bin packing |
| title_short | A tensor analysis improved genetic algorithm for online bin packing |
| title_sort | tensor analysis improved genetic algorithm for online bin packing |
| topic | Genetic Algorithm Bin Packing Problem Tensor Genetic Diversity Fixation (Popular Genetics) Natural Selection Locus (Genetics) Mutation |
| url | https://eprints.nottingham.ac.uk/33940/ https://eprints.nottingham.ac.uk/33940/ https://eprints.nottingham.ac.uk/33940/ |