Reactive Scheduling of Crude Oil using Structure Adapted Genetic Algorithm under Multiple Uncertainties
Debashish Panda, Manojkumar Ramteke
文献索引：10.1016/j.compchemeng.2018.04.005
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摘要
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.