Abstract
In today’s global economy, the oil industry plays a vital role and has an effect on most of countries within leading business environments, particularly in oil producing countries. To deal with the complexity of the crude oil supply network, a mathematical programming model is developed to formulate a crude oil supply chain. A robust optimization model is developed to maximize the profitability of the entire chain and take uncertainties of price and demand into account. The results show that according to the real case study data the robust optimization technique will increase the profitability of the crude oil supply chain.
Highlights
Crude oil as a main energy source nowadays has a vital role in today’s business
Complex studies are conducted to decide on different problems at this supply network, optimize this competitive system, and gain competitive advantages
The key issue to configure the optimal crude oil network design is the uncertainty in the price and demand
Summary
Crude oil as a main energy source nowadays has a vital role in today’s business. The most energy experts predict that world primary energy demand will double by the year 2030, increasing from 9 to 18 Gtoe. Uncertainty in demand and price for energy sources, especially crude oil, is a leading factor which should be born in mind to make more realistic decisions [1] To deal with these high uncertain parameters with difficulty in specifying scenarios, to our knowledge, the robust optimization was the most appropriate method in crude oil supply context. The main contributions of current work are as follows: spatial integration to form a comprehensive structure of the COSC, taking uncertain demands and prices into account, determining the nearoptimal solution under the robust optimization method, validating the presented mathematical programming model by providing a real case study. The reminder of this paper is organized as follows: The deterministic optimization model of the supply chain is described in Section 3, followed by a description of the robust optimization mathematical modeling Section 4
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