摘要
运用燕尾突变理论,以应急物流能力为状态变量,应急物流流量变化率、时间变化率和成本变化率为控制变量,建立应急物流能力系统突变模型,建立系统势函数确定平衡曲面、奇点集和分岐点集,讨论应急物流能力的突变临界点及稳定性,在此基础上建立非线性规划模型以控制和提升应急物流能力,并用仿真算例分析验证模型应用的可行性。通过研究本文得出三点结论:通过调查及实测可以获得三个控制变量的相关数据,确定系统的奇点集和分歧点集,进而确定系统当前状态的稳定性和突变趋势;根据应急物流需求的特点、控制变量的性质和外力作用程度对相关控制变量进行有效管理,将对应急物流能力的瞬时提升起到非常明显的作用与效果;应急物流能力系统的稳定与提升是系统工程,鉴于各控制要素在管控中活动方向有背离情况,借助Pareto思想对主要要素进行控制,可获得时间效益、流量效益和成本效益的相对平衡的非劣解。
Taking the catastrophe theory as a foundation, this paper builds a swallowtail mutation model of emergency logistics capacity system (ELCS) with emergency logistics capacity (ELC) as state variable, logistic flow change rate, logistic time change rate and logistic cost change rate as three control variables. The balance surface, singularities set and bifurcation set are ascertained by potential function. After this, the break points and its stability of ELC are discussed, based on which, the nonlinear programming models are established to control and improve ELC. At last an example is given to test the effectiveness of the model Three conclusions are educed. Firstly, the relevant data of three control variables can be measured through surveys, and the set of the singularity set and bifurcation set of system can be determined, also to determine the stability and mutation trends of current system state can be ascertained. Secondly, according to the characteristics of emergency logistics needs, the nature of control variables and the relevant external force, we manage control variables effectively, which will enhance ELC instantaneously and significantly. Lastly, to enhance the stability of ELCS is a system engineering. As the control e^ements have the deviate active direction, we manage and eon*~rol ~he main elements with Pareto thought; the non-inferior solutions for the relative balance of time-effectiveness, flow-effectiveness and cost-effectiveness can be obtained.
出处
《系统工程》
CSSCI
CSCD
北大核心
2013年第9期55-62,共8页
Systems Engineering
基金
国家自然科学基金资助项目(71073079)
江苏省社会科学基金资助项目(11EYD045)
江苏省普通高校研究生科研创新计划项目(CXLX-0174)
关键词
应急物流能力
燕尾突变模型
奇点
控制模型
Emergency Logistics Capacity~ Swallowtail Mutation Model~ Singularity~ Control Model