Abstract: To solve the multi-objective optimization problem of short-term crude oil scheduling, on the basis of four objectives in existing optimization models including the number of charging tanks, the times of charging tank switching, the mixing cost of crude oil in pipelines and the mixing cost of charging tank bottoms in a crude oil scheduling process, the model established in this paper adds an optimization objective of the energy consumption cost of crude oil transferring through pipelines, which is more coincident to real production. The extreme value archive set is introduced into Strength Pareto Evolutionary Algorithm 2 (SPEA2), while Multi-Objective Grey Wolf Optimizer (MOGWO) algorithm is combined to guide the update of the extreme value archive set to enhance the global search ability of the algorithm; the cosine similarity is adopted to prune the extreme value archive set to improve the diversity of individuals in the set. The modified algorithm is compared with several representative evolutionary multi-objective optimization algorithms, and the experimental results show that the proposed one has better performance in solving the short-term scheduling problem of crude oil.

Key words: crude oil scheduling, multi-objective optimization, SPEA2 (strength Pareto evolutionary algorithm 2), extreme value archive set