Scheduling of actual size refinery processes considering environmental impacts with multiobjective optimization

This paper deals with the scheduling problem of refinery processes considering environmental impacts. To keep abreast of rapidly changing business circumstances, the effective scheduling of the objective of which is to maximize the total profit is absolutely needed for large-scale plants such as refinery processes. In addition, companies cannot avoid making an effort to reduce environmental impacts because now people have a much better understanding of the environment. However, the two objectives mentioned above are conflicting. There is no way to maximize the total profit and minimize environmental impacts simultaneously, but a tradeoff exists. In this case, the best way is to obtain Pareto optimal solutions by multiobjective optimization. Plotting Pareto optimal solutions, decision makers are able to know the correlation between the two objectives. The selection of one of the Pareto optimal solutions depends largely on the decision makers. In this paper, a mixed-integer linear programming model is developed for solving the scheduling problem of actual size refinery processes. Critical Surface-Time 95 (CST95), an impact assessment methodology, is used for considering global environmental impacts. The ε-constraint method is used in order to implement multiobjective optimization. Finally, this paper proposes Pareto optimal solutions and shows the optimal scheduling of an arbitrary point in Pareto optimal solutions compared with the total profit maximization problem.