Dormitory Assignment Using a Genetic Algorithm
This study proposes a genetic algorithm based algorithm for assigning freshmen’s dormitory rooms according to five living habits and preferences. In the proposed genetic algorithm, we used a locally exhaustive crossover method to avoid divergence results, and then got better fitness values for this...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2021.1999595 |
| Summary: | This study proposes a genetic algorithm based algorithm for assigning freshmen’s dormitory rooms according to five living habits and preferences. In the proposed genetic algorithm, we used a locally exhaustive crossover method to avoid divergence results, and then got better fitness values for this dormitory assignment problem. In addition, we used a half-half selection strategy to reduce the time consumption during the iteration procedure. Experimental results have shown that the proposed algorithm could have acceptable performances with reasonable computational time. In addition, two counterpart methods were used to evaluate the performance of the proposed algorithm: a simulated annealing method and a random assignment method. The comparative results have also shown that 1) the execution time of the proposed algorithm was significantly less that of the simulated annealing method; 2) the fitness value of the proposed algorithm was significantly less than that of the random assignment method; 3) the fitness value of the proposed algorithm is almost the same as that of the simulated annealing method; 4) the proposed algorithm is stable to repeated executions; 5) the proposed algorithm is still suitable even when the capacities (beds) of rooms are different. |
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| ISSN: | 0883-9514 1087-6545 |