A genetic algorithm approach to short‐term scheduling of crude oil operations in refinery

Abstract

As a type of process plant, a refinery is characterized by the interaction of discrete events and continuous processes. To schedule crude oil operations in a refinery, it is necessary to define and schedule the jobs simultaneously such that heuristics and meta‐heuristics cannot be directly applied. It is very challenging to schedule crude oil operations. To solve this problem, it is decomposed into two subproblems hierarchically. At the upper level, a refining schedule is found, while at the lower level a detailed schedule is obtained to realize the refining schedule. Given a refining schedule at the upper level, this paper studies the detailed scheduling problem at the lower level. Based on a control‐theoretic perspective, the problem is innovatively transformed to a problem of assigning charging tanks to distillers such that meta‐heuristic methods can be applied. Then, a genetic algorithm (GA) approach is developed to solve the problem. In realizing the proposed GA, based on a set of existence conditions of a feasible schedule, methods are presented to guarantee that each chromosome corresponds to a feasible schedule. An industrial case study is used to show the application of the proposed method. It shows that the method works well and is applicable to real‐life problems. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.