A Variable Relationship Excavating Based Optimization Algorithm for Solving 0-1 Knapsack Problems
- Resource Type
- Conference
- Authors
- Zheng, Minyi; Gu, Fangqing; Chen, Xuesong; Wu, Hao-Tian
- Source
- 2019 15th International Conference on Computational Intelligence and Security (CIS) CIS Computational Intelligence and Security (CIS), 2019 15th International Conference on. :36-39 Dec, 2019
- Subject
- Computing and Processing
Optimization
Sociology
Statistics
Evolutionary computation
Simulation
Search problems
Maintenance engineering
Optimization algorithm, Knapsack problem, Knowledge excavating, Combinatorial optimization
- Language
The past decades have seen an extensive investigation of evolutionary algorithms. The recombination operators of most evolutionary algorithms are either single-point crossover or multi-point crossover for solving 0-1 combinatorial optimization problems. There is a little studies on excavating the variable relationship to improve the efficiency of the recombination operator. Hence, we propose an optimization algorithm based on excavating variable relationship for solving 0-1 combinational problems. The aim of the recombination operator is fully utilizing the inherent information from every slice component of all individuals. We compared the proposed algorithm with the classic evolutional algorithm with single-point crossover operation on several 0-1 knapsack problems, which is a classical combinatorial optimization problem. The simulation results show the convergence efficiency of the proposed algorithm.