Year: 2024
Type: article
Abstract: To better solve NP-complete problems, this paper proposes a Discrete Particle Swarm Optimization algorithm based on an Information Sharing Mechanism (ISM-DPSO). The algorithm uses a mechanism of sharing the pheromone of the ant colony algorithm to update particles; the particle swarm threshold function application is initialized. At the same time, to enhance the algorithm's global search ability, a particle swarm is initialized at a certain probability, and on this basis, using a nonlinear dynamic adjusting pheromone persistent rate strategy to guide the information memory. The proposed algorithm is applied to the knapsack problem with single constraints and the vehicle cargo loading problem with multiple constraints, and the optimization results are compared with the basic discrete particle swarm optimization algorithm (DPSO). The experimental results show that the ISM-DPSO algorithm outperforms the DPSO algorithm in terms of both the optimal value and the algorithm's fitted value, and the search results are superior to those of the DPSO algorithm.
Source: Kasem Bundit Engineering Journal
Institution: Muban Chombueng Rajabhat University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7215565397