Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem
The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across various geographical locations. Solving this problem demands tackling numerous scheduling and routing constraints while aiming to minimise total operational cost. One of the main obstacles in designin...
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| Format: | Conference or Workshop Item |
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IEEE Press
2017
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| Online Access: | https://eprints.nottingham.ac.uk/41542/ |
| _version_ | 1848796299108810752 |
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| author | Algethami, Haneen Landa-Silva, Dario |
| author_facet | Algethami, Haneen Landa-Silva, Dario |
| author_sort | Algethami, Haneen |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across various geographical locations. Solving this problem demands tackling numerous scheduling and routing constraints while aiming to minimise total operational cost. One of the main obstacles in designing a genetic algorithm for this highly-constrained combinatorial optimisation problem is the amount of empirical tests required for parameter tuning. This paper presents a genetic algorithm that uses a diversity-based adaptive parameter control method. Experimental results show the effectiveness of this parameter control method to enhance the performance of the genetic algorithm. This study makes a contribution to research on adaptive evolutionary algorithms applied to real-world problems. |
| first_indexed | 2025-11-14T19:45:46Z |
| format | Conference or Workshop Item |
| id | nottingham-41542 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:45:46Z |
| publishDate | 2017 |
| publisher | IEEE Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-415422020-05-04T18:48:46Z https://eprints.nottingham.ac.uk/41542/ Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem Algethami, Haneen Landa-Silva, Dario The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across various geographical locations. Solving this problem demands tackling numerous scheduling and routing constraints while aiming to minimise total operational cost. One of the main obstacles in designing a genetic algorithm for this highly-constrained combinatorial optimisation problem is the amount of empirical tests required for parameter tuning. This paper presents a genetic algorithm that uses a diversity-based adaptive parameter control method. Experimental results show the effectiveness of this parameter control method to enhance the performance of the genetic algorithm. This study makes a contribution to research on adaptive evolutionary algorithms applied to real-world problems. IEEE Press 2017-06-05 Conference or Workshop Item PeerReviewed Algethami, Haneen and Landa-Silva, Dario (2017) Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem. In: 2017 IEEE Congress on Evolutionary Computation (CEC 2017), 5-8 June 2017, San Sebastian, Spain. Genetic Algorithms Adaptive Evolutionary Algorithm Workforce Scheduling and Routing http://ieeexplore.ieee.org/document/7969516/ |
| spellingShingle | Genetic Algorithms Adaptive Evolutionary Algorithm Workforce Scheduling and Routing Algethami, Haneen Landa-Silva, Dario Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem |
| title | Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem |
| title_full | Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem |
| title_fullStr | Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem |
| title_full_unstemmed | Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem |
| title_short | Diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem |
| title_sort | diversity-based adaptive genetic algorithm for a workforce scheduling and routing problem |
| topic | Genetic Algorithms Adaptive Evolutionary Algorithm Workforce Scheduling and Routing |
| url | https://eprints.nottingham.ac.uk/41542/ https://eprints.nottingham.ac.uk/41542/ |