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Python-based optimization model and algorithm for rescue routes during gas leak emergencies

机译:基于Python的燃气泄漏紧急情况下救援路线的优化模型和算法

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Based on the theories and methods of operations research, a mathematical model for the shortest rescue route during gas leak emergencies in high-sulfur oil and gas fields is built in this paper, which contains two weights of rescue route optimization, and serves the bi-objective optimization process. An approximate search algorithm with two optimization objectives is proposed for the model based on heuristic algorithm, which could find out the shortest escape route from the double-weight escape route network by constructing auxiliary functions. Along with the study case of the gas leak emergency rescue system of the Puguang gas field in Sichuan, the algorithm procedures are introduced, the convergence rate of the algorithm are analyzed, and the time complexity and the strengths of the algorithm are discussed. By this algorithm, decision makers can find out the optimum rescue route on the distribution sketch map of the Puguang gas field, thus realizing the two optimizing targets, and providing strong technical support for gas leak rescue in the gas field.
机译:本文基于运筹学的理论和方法,建立了高硫油气田天然气泄漏事故应急救援最短路径的数学模型,该模型包含两个优先权,可以为救援工作提供最有力的支持。目标优化过程。针对基于启发式算法的模型,提出了一种具有两个优化目标的近似搜索算法,通过构造辅助函数,可以从双权逃生路线网络中找出最短的逃生路线。结合四川普光气田泄漏应急救援系统的研究案例,介绍了算法程序,分析了算法的收敛速度,讨论了算法的时间复杂度和强度。通过该算法,决策者可以在普光气田分布示意图上找到最优的救援路线,从而实现了两个优化目标,为气田的漏气救援提供了有力的技术支持。

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