Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.