圖論問題的遺傳算法：在清晰與模糊的環境中(英文)

1 Introduction
1.1 Graph Algorithms
1.2 Computational Complexities of Algorithms
1.3 Graph Theoretic Definitions and Notations
1.4 Genetic Algorithms
1.4.1 Components of a GA
1.4.2 General structure of a GA
1.5 Theoretical Foundation of GAs
1.5.1 Schemata and building blocks
1.5.2 GAs and traditional search methods
1.6 Arithmetic of Imprecise Numbers
1.6.1 Interval number and interval arithmetic
1.6.2 Triangular fuzzy number and its arithmetic...

2 Maximum Weight Independent Set of a Graph
2.1 Introduction
2.2 0-1 Integer Programming Formulation
2.3 The GA for the MWIS Problem
2.3.1 Genetic representation
2.3.2 Fitness function
2.3.3 Population initialization
2.3.4 Selection
2.3.5 Crossover
2.3.6 Mutation
2.4 Computational Results
2.5 A summary

3 Minimum Weight Dominating Set of a Graph
3.1 Introduction
3.2 0-1 Integer Programming Formulation
3.3 The GA for the MWDS Problem
3.3.1 Genetic representation
3.3.2 Fitness function
3.3.3 Population initialization
3.3.4 Selection
3.3.5 Crossover
3.3.6 Mutation
3.4 The Proposed GA and its Efficiency
3.5 Computational Results
3.6 A Summary

4 p-center and p-radius of a Graph in Crisp and Fuzzy Environments
4.1 Introduction
4.2 Genetic Representations and Operators
4.2.1 Representations
4.2.2 Initialization
4.2.3 Fitness function
4.2.4 Selection
4.2.5 Crossover
4.2.6 Mutation
4.3 Computational Result
4.4 Fuzzy Network and Different Location Models
4.5 Comparison of Imprecise Numbers