원문정보
초록
영어
This paper focuses on the approach to solve the immune evolution optimization with interval number judgment matrix weight vector. In light of the features of interval number judgment matrix, we transform the solution problem of weights into the optimization one of nonlinear with restriction, design immune evolution algorithm on the base of immune mechanism, and use the convergence ability of immune system to search the optimal access to get interval numbers from matrix weight vector. Moreover, we construct immune operator and form vaccine and optimization strategies by priori knowledge of target problem, by which we can keep individual diversity and elite individuals and abandon useless individuals as soon as possible. In the evolution process, search can be dramatically improved by overcoming the problems of earliness and degradation during global search. Simulation results of experiments show the advantages of this algorithm in accuracy, convergence, convergence rate and so on.
목차
1. Introduction
2. Classic ahp to Solve Judgment Matrix Weight
2.1. Judgment Matrix and its Scale Selection
2.2. Acquisition of Weight Vector
3. Optimization Model and Immune Evolution Algorithm of Solving Interval Number Weight Vector
3.1. Demonstration of Interval Number of Judgment Matrix and its Weight Vector
3.2 Optimization Model of Immune Evolution
4. Design of Algorithm
5. Conclusion
Acknowledgements
References