Chance Constraint Programming and PSO Techniques for a Multilevel Uncertain Transportation in Supply Chain Model

The traffic engineering management optimization problem has important component as supply chain optimization and transportation problem. In this investigation, we the shipping costs over a three tiered distribution system comprising of plants to the distribution corners to the customers, is optimized. Several plants produce multiple commodities that are shipped to distribution corners together with a fixed cost. From a distribution corner commodities are supplied to the customers. Evidently the variables such as supply capacities, demands in the model caries some uncertainty in the practical decision environment, this paper treated the supply capacities, demands. Then the uncertain transportation problem was reformulated as deterministic model by using different type of chance-constrained programming techniques. Soft computing technique like Particle swarm optimization (PSO) is used to solve numerically converting the model to deterministic model. To illustrate numerically the application and effectiveness of the proposed model.