Abstract
After the oil market in Taiwan has been opened to the private enterprise, the oil refinery industries in Taiwan have not only entered a completely free market, but also faced the challenge from world competition. In such an environment, there exist varieties of uncertain factors which have caused the failure of traditional production planning model. Therefore, to increase compatibility, it is essential to increase efficiency in the inventory, production, transportation and profit.Refineries begin to gain revenues when their products are sold in the market. This research examines the possible costs of additional inventories or recurrent times of refineries derived from early or late shipment in a continuous production system. Meanwhile, we shall develop a responsive and flexible production planning system to cope with uncertain manufacturing factors. Then, based on the developed mathematical programming model, an optimal production structure with the minimum total cost of production, inventory and start-up is proposed. Tolerance analysis is conducted to cope with the uncertain environment. Furthermore, in order to clarify the uncertain demand and cost, Fuzzy Set Theory is adopted to develop a fuzzy linear programming (FLP) model, so that a maximal profit production strategy is proposed with highest degree of satisfaction.Then, we would conduct a case study on CPC Corporation, Taiwan (CPC). For the purpose of more general application, the issues of large-scale cases have been taken into account so that if the model scale is too large, the corporation can use a heuristic approach to find the near optimal solutions. In this research, we shall adopt the soft computing technique, in particular, the Particle Swarm Optimization (PSO) algorithm, to propose time-effective solution procedure for the proposed models.It is expected that the results of this research will be able to provide useful information towards developing cost and profit-effective oil refinery strategies in an uncertain environment.