Operations research: an introduction, 4th ed.
Operations research: an introduction, 4th ed.
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Data Structures and Algorithms
Data Structures and Algorithms
Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators
Artificial Intelligence Review
A Hybrid Genetic Algorithm for Highly Constrained Timetabling Problems
Proceedings of the 6th International Conference on Genetic Algorithms
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This paper presents the hybridization of the Genetic Algorithm (GA) by using ideas enclosed in exact techniques, like the Branch and Bound (B&B), Minimal Spanning Tree and Backtracking Algorithms. It also has been used the Divide and Conquer principle. Two crossovers operators were proposed to propagate the good schema. These operators together with mutation and one method to generate the initial population are based on the algorithms mentioned above.This Hybrid GA was applied to the well-known combinatorial optimization problem Traveling Salesman Problem (TSP). In almost all cases, the optimal solution was found in few generations with quite a few individuals.The Hybrid GA was implemented in software by using Visual C++ 6.0 together with VTK library (tool for scientific visualization). VTK was used to build a visual environment which allows to see how is working the Hybrid GA.