A Combining Genetic Learning Algorithm and Risk Matrix Model Using in Optimal Production Program

One of the important issues for any enterprises is the compromise optimal solution between inverse of multi objective functions. The prediction of the production cost and/or profi t per unit of a product and deal with two obverse functions at same time can be extremely diffi cult, especially if there is a lot of confl ict information about production parameters. But the most important is how much risk of this compromise solution. For this reason, the research intrduce and developed a strong and cabable model of genatic algorithim combinding with risk mamagement mtrix to increase the quality of decisions as it is based on quantitive indicators, not on qualititive evaluation. Research results show that integration of genetic algorithim and risk mamagement matrix model has strong signifi cant in the decision making where it power and time to make the right decesion and improve the quality of the decision making as well.