本文選題：危險品運輸 + 級聯(lián)失效　； 參考：《計算機仿真》2017年08期

【摘要】：為減小危險品運輸事故導致的人身傷亡和財產損失數(shù)目,減弱事故級聯(lián)效應造成的交通擁堵。建立關于危險品運輸安全性的路徑選擇模型,以危險品運輸事故級聯(lián)失效導致的交通擁堵最小、危險品運輸事故影響的人口最少及危險品運輸?shù)目傎M用最少為目標,構建多目標優(yōu)化模型。多目標問題求解的難點在于求解具有收斂性的pareto最優(yōu)解集,因此,采用改進的帶精英策略的非支配排序遺傳算法(NSGA-Ⅱ)對模型求解。以供應點選擇多種車輛運輸多種危險品到需求點為運輸案例驗證模型和算法的可靠性。結果表明利用NSGA-Ⅱ算法可以獲得危險品運輸路徑和車輛使用的一系列pareto最優(yōu)解集,解集的空間分布均勻且具有收斂性和魯棒性。驗證了模型和算法的可靠性,可以為危險品運輸提供決策支持。
[Abstract]:In order to reduce the number of casualties and property losses caused by dangerous goods transportation accidents, traffic congestion caused by cascading accidents is reduced. A route selection model for the safety of dangerous goods transportation is established, which aims at minimizing traffic congestion caused by cascading failure of dangerous goods transportation accidents, minimizing the population affected by dangerous goods transportation accidents, and minimizing the total cost of dangerous goods transportation. Multi-objective optimization model is constructed. The difficulty of solving multi-objective problem is to solve the convergent pareto optimal solution set. Therefore, an improved non-dominated sorting genetic algorithm (NSGA- 鈪，

本文編號：2117524