原油移动路径规划是原油调度中至关重要的子任务，直接影响到生产过程中原油供给的稳定性和付油的高效性。由于此任务需要考虑大规模罐区内复杂的设备条件，并受到严格的工业生产约束，同时需要兼顾途径阀门数量与泵机组运力，导致目前依然倚重调度人员的人工经验来制定路径规划方案，对传统算法和进化算法的应用提出了挑战。据此，本研究基于有向图结构对大规模原油罐区进行细致数学建模，并提出一种基于偏好的原油移动路径多目标优化(Preference-based multi-objective optimization for crude oil movement path，PB-MOO)算法，突破了过去高度依赖人工方法的局限性，为原油移动路径规划提供智能化解决方案。实验证明该算法能够在满足实际约束的条件下，找到复杂任务的高质量候选解，验证了其在此领域的可行性和有效性。
A Preference-based Multi-objective Optimization for Crude Oil Movement Path
The planning of crude oil movement path is a crucial subtask within crude oil scheduling,directly im-pacting the stability of crude oil supply and the efficiency of oil delivery in the production process.Given the need to consider complex equipment conditions within large-scale tank areas and strict industrial production constraints,while also balancing the number of valves along the route with pump unit capacity,the current reliance on manual experience of schedulers for developing path planning schemes poses a challenge to the application of traditional al-gorithms and evolutionary algorithms.Therefore,this study undertakes a meticulous mathematical modeling of large-scale crude oil tank areas based on directed graph structures.It proposes a preference-based multi-objective optimization algorithm for crude oil movement path(PB-MOO),overcoming the limitations associated with past heavily manual methods and providing an intelligent solution for crude oil movement path planning.Experimental results demonstrate that the algorithm can identify high-quality candidate solutions for complex tasks while meet-ing practical constraints.This validates its feasibility and effectiveness in this field.
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