Production and distribution plan for fresh produce under random fuzzy environment

摘要

This paper addresses the problem of production and distribution for fresh produce. A two stage minimum risk production and distribution planning model of agricultural products, which embeds the chance objective function, is proposed to handle the uncertainty of crops' yields that are assumed to be characterized by random fuzzy variables with known probability and possibility distributions. The two-stage random fuzzy minimum risk programming selected is that the decisions in a first stage are designed to meet the uncertain outcomes in a second stage. Since it is always difficult to handle with the random fuzzy model directly, we apply an Approximation Approach (AA) to evaluate the value of the objective function. Considering that the approximating model is neither linear nor convex, it can't be solved via the conventional optimization algorithm. Therefore, an approximate-based Hybrid Particle Swarm Optimization (PSO) algorithm is designed to solve the proposed model. Finally, an application example is presented to illustrate the significance of the random fuzzy production and distribution model as well as the effectiveness of the solution method.