Fuzzy random chance-constrained programming

By fuzzy random programming, we mean the optimization theory dealing with f uzzy random decision problems. This paper presents a new concept of chance of fuzzy random events and then constructs a general framework of fuzzy ran dom chance-constrained programming (CCP). We also design a spectrum of fuzz y random simulations for computing uncertain functions arising in the area of fuzzy random programming. To speed up the process of handling uncertain functions, we train a neural network to approximate uncertain functions bas ed on the training data generated by fuzzy random simulation. Finally, we i ntegrate fuzzy random simulation, neural network, and genetic algorithm to produce a more powerful and effective hybrid intelligent algorithm for solv ing fuzzy random programming models and illustrate its effectiveness by som e numerical examples.