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Volume 10 article 232 pages: 147 - 152
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.
C. McNair: Defi ning and Shaping the Future of Cost Management, Journal of Cost Management, Vol. 14, No. 5, 2000, pp. 28-32, ISSN 1092-8057.
Eckart, Z., Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications. PhD thesis, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, November 1999.
Glover F., Kelly J.P., Laguna M., New Advances for Wedding Optimization and Simulation, Proceedings of the 1999 Winter Simulation Conference, 1999.
J. Fraser, B.J. Simskins: Enterprise risk management: Today’s Leading Research and Best Practices for Tomorrow’s Executives, John WIley & Sons, ISBN 978-0-470-49908-5, USA, 2010.
J. Sanchis, et al.:A new perspective on multiobjective optimization by enhanced normalized normal constraint method, Structural and Multidisciplinary Optimization, 2008, Vol. 36, No. 5, pp. 537–546, ISSN 1615-1488.
L. Chi-Ming, G.Mitsuo: An Effective Decision- Based Genetic Algorithm Approach to Multiobjective Portfolio Optimization Problem, Applied Mathematical Sciences, 2007, Vol. 1, No. 5, pp. 201 – 210, ISSN 0066-5452.
Miettinen, K., Nonlinear multi-objective optimization. Springer, 1999.
N. Fafandjel, A. Zamarin, M. Hadjina: Shipyard production cost structure optimization model related to product type, International Journal of Production Reasearch, 2010, Vol. 48, No. 5, pp. 1479-1491, ISSN 0020-7543.
S. Utyuzhnikov, P. Fantini, M. Guenov: A method for generating a well- distributed Pareto set in nonlinear multi-objective optimization, Journal of Computational and Applied Mathematics, 2009, Vol. 223, No. 2, pp. 820–841, ISSN 0377-0427.
The CAS Enterprise Risk Management Committee: Overview of Enterprise Risk, Management,Casualty Actuarial Society Forum, 2003, Pages 99-164, ISSN 1046-6487