Improved Ant Colony Algorithm for Solving Multi-modal Resource Constrained Project Scheduling Problem
- Resource Type
- Conference
- Authors
- Chen, Jie; Hao, Wenqian; Dong, Yixi
- Source
- 2022 International Conference on Big Data, Information and Computer Network (BDICN) BDICN Big Data, Information and Computer Network (BDICN), 2022 International Conference on. :6-11 Jan, 2022
- Subject
- Computing and Processing
Computational modeling
Process control
Big Data
Mathematical models
Scheduling
Computer networks
Standards
component
multi-mode
resource constraints
project scheduling
ant colony algorithm
adaptive parameters
- Language
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.