Solving Fuzzy Chance-Constrained Programming with Ant Colony Optimization-Based Algorithms and Application to Fuzzy Inventory Model
An ant colony optimization algorithm is designed to solve continuous optimization models. Based on this algorithm, a hybrid intelligent algorithm combined with fuzzy simulation and neural network is introduced for solving fuzzy chance constrained models. Several numerical examples are given to show the algorithms effective. As an application, a fuzzy inventory model is established and solved with the hybrid intelligent algorithm.
Unable to display preview. Download preview PDF.