Solving Multi-robot Task Assignment Problem based on Improved Genetic Algorithm
Aiming at the low efficiency of robot task distribution and unbalanced task distribution in the process of warehouse task scheduling, this paper aims at minimum total task path and balanced task distribution, establishes a warehouse robot scheduling scheme and mathematical model, and proposes an improved genetic algorithm for task allocation. Firstly, greedy algorithm is introduced to optimize the initial population and improve the quality of the initial population. Secondly, the heuristic bidirectional triple crossover operator is designed to expand the search range of the population and improve the accuracy of the optimal solution. Finally, the multi-variant strategy is introduced to solve the problem that the algorithm falls into local optimality. The experimental results show that the improved algorithm has better convergence and balanced distribution ability.
Authors
- Zhibin Wang (ORCID: https://orcid.org/0000-0001-7618-7973)
- Jianjun Zhu (ORCID: https://orcid.org/0000-0002-7681-4241)
Institutions
- Jilin University of Chemical Technology (CN)
Publication Details
- Journal
- Frontiers in Computing and Intelligent Systems
- Published
- 2024-12-29
- DOI
- https://doi.org/10.54097/sctr7h26
- Citations
- 1
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- People's Government of Jilin Province