A heuristic genetic algorithm methodology

The family of combinatorial optimization problems is characterized by having a finite number of feasible solutions. These problems abound in everyday life, particularly in engineering design. In principle, finding the optimal solution for a finite problem could be done by simple enumeration. However, real life problems are much more complicated and enumeration is frequently an impossible technique to use because the number of feasible solutions call be enormous. This article will propose a methodology for using GA in solving complex combinatorial optimization problems. A classification scenario is used as an example.