Research on the Dual-Objective Scheduling of the Pipeline Path of Liquid Terminal Resources Based on a Hybrid Algorithm

Abstract

With the daily use of liquid cargoes such as crude oil and their derivatives, the global transportation of liquid cargoes has developed rapidly. Liquid cargoes are mainly transported via tankers and pipelines. In the liquid terminal, the handling operations and internal transportation operations are conducted using oil transfer arms and pipelines, and the pipeline path of the cargo is selected using valves. The number of times a valve opens and closes and the length of pipeline paths are the main factors that affect handling time and cost. In addition, different types of valves have different operating costs and levels of operating energy consumption. At this stage, most of the valve selection work is still manually completed, which consumes a lot of time and generates high labor costs, and the actual operation efficiency is low. In this paper, the cargo unloading pipeline path is the main research object, the problem of oil transfer arms–valves–pipeline (PAVP) is proposed, and a dual-objective model is established, accounting for total time in port and the unloading cost of the vessel. An NSGA-II-Dijkstra hybrid algorithm is employed to solve the PAVP, and the improved algorithm (INIIDA) is designed to improve the solution speed via an adaptive dynamic probability based on the Pareto level and heaps in the shortest path. The results show that the INIIDA could better address the PAVP than the NSGA-II-Dijkstra hybrid algorithm. Innovative fusion algorithms are employed to improve the efficiency of port operations.