The modeling and optimization of an industrial-scale crude distillation unit(CDU)are addressed.The main specifications and base conditions of CDU are taken from a crude oil refinery in Wuhan,China.For modeling of a complicated CDU,an improved wavelet neural network(WNN)is presented to model the complicated CDU,in which novel parametric updating laws are developed to precisely capture the characteristics of CDU.To address CDU in an economically optimal manner,an economic optimization algorithm under prescribed constraints is presented.By using a combination of WNN-based optimization model and line-up competition algorithm(LCA),the superior performance of the proposed approach is verified.Compared with the base operating condition,it is validated that the increments of products including kerosene and diesel are up to 20% at least by increasing less than 5% duties of intermediate coolers such as second pump-around(PA2)and third pump-around(PA3).
A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing.Firstly,hierarchical scheduling strategy is presented for solving the former sub-problem,where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages,and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective.Line-up competition algorithm(LCA)is presented to find out optimal order sequence and order assignment rule,which can minimize total flow time or maximize total weighted process time.Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders.Moreover,with the problem size increasing,the solutions obtained by the proposed approach are improved remarkably.The proposed approach has the potential to solve large size MMSP.
