Intelligent Engine for Supply and Transportation of Oil Productions

Discrete Event simulation (DES), mathematical programming (MP) and analysis of variance (ANOVA) are among the popular tools in operational research (OR) used in dynamic industry like petroleum industry. The integration of these methods even becomes more significant to managerial application in the industry. The objective of this project is to present an integrated decision support system by which a decision maker should be able to choose the optimal number of tanks, tank size and truck arrival rate to maximize average total profit and minimize the total transportation cost for an oil refinery terminal operations. The Intelligent Engine for Supply and Transportation of Petroleum (IESTP) is developed using a discrete-event simulation program in ARENA software, mathematical linear programming (LP) in I-Log software and analysis of variance (ANOVA) in SPSS software, these models are combined in a complex program developed using visual basic software (VB). An optimization model was formulated with the objective to minimize the total transportation cost. In the model formulation, hard constraints were considered and the linear programming (LP) technique was used. Result obtained suggests the use of certain types of trucks can reduce the operation costs, if compared to that of the current situation. The reduction of costs is due to the reduction of traveling trips as based on the problem constraints. Overall, output of this project has given positive impacts on the transportation operations. The effect of the changes can help the management of an oil company to make efficient decisions. The IESTP is able to predict with 99 % confidence a set of factor levels that yields the highest average total profit