Solving shortest circuit problem of military health support based on partheno-genetic algorithm
10.3724/SP.J.1008.2009.00074
- Author:
Xing-Bo JIANG
1
Author Information
1. Department of Military Health Service
- Publication Type:Journal Article
- Keywords:
K-random-nearer-neighbor algorithm;
Partheno genetic algorithm;
The shortest circuit problem of health support;
Traveling salesman problem
- From:
Academic Journal of Second Military Medical University
2010;31(1):74-79
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To propose an effective algorithm for solving the shortest circuit problem of military health support. Methods: Partheno-genetic algorithm (PGA), which only used mutation operation and selection operation, was adopted in the present study. The algorithm was based on K-random-nearer-neighbor algorithm combined with two-random-point exchange, two-neighbor-point exchange, circular-based part inversion and random insertion mutation operations. Furthermore, greedy strategy was applied in selection to improve the hill-climbing capability of PGA. Results The simulation results of CTSP31 and standard dataset from TSP library indicated that the PGA was more effective than existing algorithms from the literature. Conclusion: PGA can serve as a basis for further development of a computer-assisted program, and it provides optimized decision-making scheme for improving the quality and speed of military medical service disposition.
