Application of an improved ant colony optimization algorithm of hybrid strategies using scheduling for patient management in hospitals.

ABSTRACT: To balance the convergence speed and solution diversity and enhance optimization performance when addressing large-scale optimization problems, this research study presents an improved ant colony optimization (ICMPACO) technique. Its foundations include the co-evolution mechanism, the multi-population strategy, the pheromone diffusion mechanism, and the pheromone updating method. The suggested ICMPACO approach separates the ant population into elite and common categories and breaks the optimization problem into several sub-problems to boost the convergence rate and prevent slipping into the local optimum value. To increase optimization capacity, the pheromone update approach is applied. Ants emit pheromone at a certain spot, and that pheromone progressively spreads to a variety of nearby r

SUBMITTER: Rahman Lingkon ML 

PROVIDER: S-EPMC11693920 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature