Improved Ant Colony Algorithm for Solving Multi-modal Resource Constrained Project Scheduling Problem

被引:0
|
作者
Chen, Jie [1 ]
Hau, Wenqian [1 ]
Dong, Yixi [2 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Econ & Management, Nanjing, Peoples R China
[2] Washington Univ, St Louis, MO USA
来源
2022 INTERNATIONAL CONFERENCE ON BIG DATA, INFORMATION AND COMPUTER NETWORK (BDICN 2022) | 2022年
关键词
component; multi-mode; resource constraints; project scheduling; ant colony algorithm; adaptive parameters;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Solving the multi-mode resource-constrained project scheduling problem is an NP-hard combinatorial optimization problem with various practical application backgrounds. Aiming at the balance between the ant colony algorithm's convergence speed and the diversity of solutions, this paper proposes an improved ant colony algorithm to solve this problem. The parameter range and change range in the algorithm can be adjusted synchronously and adaptively with the operation of the algorithm. The positive feedback process of the pheromone volatilization factor control algorithm is improved. Simultaneously, the maximum and minimum ant system algorithm and the upper and lower limits of the pheromone are introduced into the ant colony algorithm to optimize the updated strategy of pheromone.
引用
收藏
页码:6 / 11
页数:6
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