Simulation Analysis of Global Optimization Algorithms as Tools for Solving Chance Constrained Programming Problems
نویسنده
چکیده
In the paper a chance constrained linear programming problem is considered in the case of join chance constraints with random both left and right hand sides. It is assumed that due to its complex stochastic nature the problem cannot be reduced to any equivalent deterministic problem. In such a case a Monte Carlo method combined with Global Optimization (GO) algorithms are proposed to solve the problem. A performance of various types of GO algorithms as tools for solving such problems are compared via computer simulations. The simulation results are presented and discussed in the paper.
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تاریخ انتشار 2012