Crude oil processed in marine access refineries contributes about 15% of the total energy production worldwide. An optimized schedule of crude unloading and charging in these offers the best utilization of available resources to increase the profitability and also helps in incorporating the future uncertainties commonly encountered in the operation. In the present study, a new reactive crude oil scheduling methodology is developed for marine-access refinery using a structured adapted genetic algorithm to handle the commonly encountered uncertainties of increase in demand and ship arrival delay. Three different industrial examples with 21, 21 and 42 periods are solved for above uncertainties with single and multiple objectives. In the single-objective formulation, profit is maximized whereas in multi-objective formulation an additional objective of inter-period deviation in crude flow to distillation units is minimized. The results obtained show the efficient handling of uncertainties with improved profitability and operability of the plant.

在海上通道精炼厂中加工的原油约占全球能源总产量的15％。其中最优化的原油装卸时间表可提供对可用资源的最佳利用，以提高盈利能力，并且还有助于整合运营中通常遇到的未来不确定性。在本研究中，使用结构化的自适应遗传算法为海上通道炼油厂开发了一种新的反应性原油调度方法，以应对需求增加和船舶到达延迟的常见不确定性。针对具有单个和多个目标的上述不确定性，解决了具有21、21和42个周期的三个不同的工业示例。在单目标表述中，利润最大化，而在多目标配方中，到蒸馏装置的原油流量的期间间偏差的附加目标最小。获得的结果表明有效处理不确定性，提高了工厂的盈利能力和可操作性。