A COMBINING GENETIC LEARNING ALGORITHM AND RISK MATRIX MODEL USING IN OPTIMAL PRODUCTION PROGRAM

Mirjana Misita; Galal Senussi; Marija Milanović

doi:10.5937/jaes10-2523

Mirjana Misita Doc. dr Mirjana Misita Univerzitet u Beogradu Mašinski Fakultet
Galal Senussi Industrial Engineering Department, Omar El-Mohktar University, El-Baitha,Libya;b,cIndustrial Engineering Department
Marija Milanović Univerzitet u Beogradu Mašinski Fakultet

DOI: https://doi.org/10.5937/jaes10-2523

Keywords: Costs, Matrix, Optimum production program, Risk Management, Genetic Algorithm, Multi-objective function,

Abstract

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 profit per unit of a product and deal with two obverse functions at same time can be extremely difficult, especially if there is a lot of conflict 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 significant in the decision making where it power and time to make the right decesion and improve the quality of the decision making as well.

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