基于運(yùn)輸情景的多式聯(lián)運(yùn)路徑規(guī)劃優(yōu)化建模方法研究
發(fā)布時(shí)間：2018-09-14 18:35
【摘要】：國家經(jīng)濟(jì)社會(huì)的可持續(xù)發(fā)展需要高效的貨物運(yùn)輸系統(tǒng)予以支撐。隨著我國綜合運(yùn)輸體系的不斷完善,作為一種先進(jìn)的運(yùn)輸組織形式,多式聯(lián)運(yùn)在運(yùn)輸實(shí)踐中得到了極大的推廣應(yīng)用,多式聯(lián)運(yùn)服務(wù)網(wǎng)絡(luò)日趨成熟,運(yùn)輸?shù)慕?jīng)濟(jì)效益和社會(huì)效益也得到了顯著提升。多式聯(lián)運(yùn)服務(wù)網(wǎng)絡(luò)的高效運(yùn)行與管理離不開科學(xué)合理的運(yùn)輸規(guī)劃。在多式聯(lián)運(yùn)服務(wù)網(wǎng)絡(luò)“戰(zhàn)略—戰(zhàn)術(shù)(網(wǎng)絡(luò)設(shè)計(jì))—運(yùn)營”三層規(guī)劃體系中,運(yùn)營層面中的路徑優(yōu)化直接面向客戶多樣化的運(yùn)輸需求,是多式聯(lián)運(yùn)服務(wù)網(wǎng)絡(luò)經(jīng)濟(jì)性、時(shí)效性和可靠性等性能的直觀體現(xiàn),因而具有十分重要的研究意義與實(shí)踐價(jià)值,也是運(yùn)輸規(guī)劃領(lǐng)域的熱點(diǎn)問題之一。而當(dāng)前多式聯(lián)運(yùn)路徑規(guī)劃既有研究在優(yōu)化建模和算法設(shè)計(jì)上存在的不足嚴(yán)重制約了其為實(shí)際問題提供決策支持的可行性�；诖�,本文從系統(tǒng)工程的角度出發(fā),綜合考慮優(yōu)化對(duì)象、運(yùn)輸服務(wù)模式、網(wǎng)絡(luò)能力、商品流完整性、優(yōu)化準(zhǔn)則以及求解方法六項(xiàng)問題規(guī)劃特征,從基礎(chǔ)運(yùn)輸情景建模入手,根據(jù)貨物性質(zhì)(以普通集裝箱為代表的常規(guī)貨物和以危險(xiǎn)品為代表的非常規(guī)貨物)對(duì)多式聯(lián)運(yùn)路徑規(guī)化問題進(jìn)行細(xì)分,進(jìn)一步系統(tǒng)研究了多式聯(lián)運(yùn)路徑規(guī)劃復(fù)雜運(yùn)輸情景建模及精確求解策略設(shè)計(jì)問題。本文的研究工作主要有下幾個(gè)方面:(1)在問題規(guī)劃方面,本文綜合分析了多式聯(lián)運(yùn)路徑規(guī)劃問題的六項(xiàng)規(guī)劃特征。尤其針對(duì)“運(yùn)輸服務(wù)模式設(shè)定”這一特征,本文在分析多式聯(lián)運(yùn)服務(wù)網(wǎng)絡(luò)系統(tǒng)的基礎(chǔ)上,重點(diǎn)研究了兩類運(yùn)輸服務(wù)模式,即以公路運(yùn)輸服務(wù)為代表的靈活運(yùn)營的服務(wù)模式和以鐵路運(yùn)輸服務(wù)為代表基于開行方案的服務(wù)模式,進(jìn)而歸納、總結(jié)了列車開行方案對(duì)多式聯(lián)運(yùn)路徑規(guī)劃的時(shí)空約束,從而將優(yōu)化建模中的運(yùn)輸服務(wù)模式設(shè)定由單運(yùn)輸服務(wù)模式擴(kuò)展到多運(yùn)輸服務(wù)模式上來,這也是論文的重要?jiǎng)?chuàng)新點(diǎn)之一。(2)在優(yōu)化建模方面,本文首先研究了單商品流、單運(yùn)輸服務(wù)模式以及單目標(biāo)優(yōu)化等設(shè)定下的多式聯(lián)運(yùn)路徑規(guī)劃基礎(chǔ)問題的優(yōu)化建模,構(gòu)建了0-1整數(shù)線性規(guī)劃模型,并將該模型應(yīng)用于多式聯(lián)運(yùn)路徑規(guī)劃對(duì)供需變動(dòng)的敏感性分析上,根據(jù)定量計(jì)算分析,得到有助于供需雙方規(guī)劃多式聯(lián)運(yùn)路徑,組織多式聯(lián)運(yùn)的若干運(yùn)輸策略。然后,基于基礎(chǔ)運(yùn)輸情景問題的“點(diǎn)—弧”建模方法,本文以普通集裝箱和危險(xiǎn)品兩類最具代表性的貨物品類為研究對(duì)象,考慮多商品流/危險(xiǎn)品流規(guī)劃、多運(yùn)輸服務(wù)模式設(shè)定以及模糊列車載運(yùn)能力設(shè)定,首先以多商品流廣義費(fèi)用最優(yōu)化為目標(biāo),構(gòu)建了復(fù)雜運(yùn)輸情景下普通集裝箱多式聯(lián)運(yùn)路徑規(guī)劃問題的混合機(jī)會(huì)約束整數(shù)非線性規(guī)劃模型,繼而采用高斯煙羽模型和箱型模型對(duì)多式聯(lián)運(yùn)服務(wù)網(wǎng)絡(luò)中的社會(huì)風(fēng)險(xiǎn)和環(huán)境風(fēng)險(xiǎn)進(jìn)行了分析與度量,構(gòu)建了環(huán)境風(fēng)險(xiǎn)閾值約束下的危險(xiǎn)品多式聯(lián)運(yùn)路徑規(guī)劃問題的“廣義費(fèi)用—社會(huì)風(fēng)險(xiǎn)”雙目標(biāo)混合機(jī)會(huì)約束整數(shù)非線性規(guī)劃模型。(3)在求解方法設(shè)計(jì)和案例優(yōu)化分析方面,本文致力于精確求解策略的設(shè)計(jì),也即首先識(shí)別非線性規(guī)劃模型中的非線性部分,然后進(jìn)行線性化轉(zhuǎn)化,得到與之等價(jià)的線性規(guī)劃模型,最后采用經(jīng)典的精確求解算法(例如分支定界法)在數(shù)學(xué)規(guī)劃軟件(例如LINGO)中進(jìn)行問題的仿真求解。而針對(duì)危險(xiǎn)品多式聯(lián)運(yùn)路徑規(guī)劃雙目標(biāo)優(yōu)化問題,本文采用集成模型線性化轉(zhuǎn)化與標(biāo)準(zhǔn)化加權(quán)求和法的求解策略進(jìn)行求解,得到雙目標(biāo)優(yōu)化問題的帕累托邊界。最后,本文以大規(guī)模實(shí)例為證,驗(yàn)證了兩類復(fù)雜運(yùn)輸情景建模問題中優(yōu)化模型與精確求解策略處理實(shí)際問題時(shí)的可行性,同時(shí)在優(yōu)化結(jié)果分析中采用敏感性分析法和模糊模擬法對(duì)實(shí)例中多式聯(lián)運(yùn)路徑規(guī)劃優(yōu)化結(jié)果與相關(guān)模型參數(shù)(包括模糊機(jī)會(huì)約束置信值和環(huán)境風(fēng)險(xiǎn)閾值)之間的關(guān)系進(jìn)行了探討,總結(jié)了多式聯(lián)運(yùn)路徑規(guī)劃優(yōu)化結(jié)果隨參數(shù)設(shè)定變動(dòng)的變化規(guī)律。
[Abstract]:The sustainable development of national economy and society needs the support of efficient freight transportation system.With the continuous improvement of China's comprehensive transportation system,as an advanced form of transport organization,multimodal transport has been greatly promoted and applied in transportation practice.The network of multimodal transport service is becoming more and more mature,and the economic and social benefits of transportation are becoming more and more mature. Efficient operation and management of the multimodal transport service network can not be separated from scientific and rational transport planning. In the three-tier planning system of the multimodal transport service network "strategy-tactics (network design) -operation", the route optimization at the operational level is directly oriented to the diversified transport needs of customers, and it is a multimodal transport service. It is of great significance and practical value to study the economic, timeliness and reliability of service network, and it is also one of the hot issues in the field of transportation planning. Based on the feasibility of decision support, this paper, from the perspective of system engineering, comprehensively considers the six planning features of optimization object, transportation service mode, network capability, commodity flow integrity, optimization criteria and solving methods, starts with the basic transport scenario modeling, and according to the nature of goods (conventional goods represented by ordinary containers). And the non-conventional goods represented by dangerous goods are subdivided into several parts, and the modeling of complex transportation scenarios and the design of exact solution strategies for multimodal transport path planning are further studied systematically. Six planning features of the route planning problem. Especially in view of the characteristics of "transportation service mode setting", this paper focuses on two types of transportation service modes based on the analysis of the multimodal transport service network system, i.e. the flexible operation service mode represented by highway transportation service and the open service mode represented by railway transportation service. The service mode of the train operation scheme is summarized, and the space-time constraints of the train operation scheme on the multimodal transport path planning are summarized. Thus, the transportation service mode setting in the optimization modeling is extended from the single transport service mode to the multi-transport service mode. This is also one of the important innovations of this paper. (2) In the optimization modeling, this paper first introduces the optimization model. This paper studies the optimization modeling of the basic problems of multimodal transport path planning under the assumptions of single commodity flow, single transportation service mode and single objective optimization. A 0-1 integer linear programming model is constructed. The model is applied to the sensitivity analysis of multimodal transport path planning to the changes of supply and demand. According to the quantitative calculation and analysis, it is helpful to supply and demand. Then, based on the "point-arc" modeling method of the basic transport scenario problem, this paper takes the two most representative types of goods, ordinary containers and dangerous goods, as the research object, considering the multi-commodity/dangerous goods flow planning, multi-transportation service mode setting and so on. Firstly, a mixed chance-constrained integer nonlinear programming model for routing problem of general container multimodal transport under complex transport scenarios is constructed with the objective of generalized cost optimization of multi-commodity flow. Then, Gaussian plume model and box model are used to analyze the social risk in multimodal transport service network. The environmental risk is analyzed and measured, and the "generalized cost-social risk" dual-objective mixed chance-constrained integer nonlinear programming model for the path planning problem of multimodal transport of dangerous goods with environmental risk threshold constraints is constructed. (3) In the design of solution methods and case optimization analysis, this paper focuses on the exact solution strategy. Design, that is to say, first identify the nonlinear part of the nonlinear programming model, then linearize the transformation, get the equivalent linear programming model, and finally use the classical exact solution algorithm (such as branch and bound method) in the mathematical programming software (such as LINGO) to solve the problem simulation. In this paper, the Pareto boundary of the bi-objective optimization problem is obtained by solving the bi-objective optimization problem with the strategy of linearization transformation of integrated model and standardized weighted summation. Finally, a large-scale example is given to verify the practical application of the optimization model and the exact solution strategy in two kinds of complex transportation scenario modeling problems. At the same time, sensitivity analysis method and fuzzy simulation method are used to analyze the feasibility of the problem, and the relationship between the optimal results of multimodal transport path planning and the parameters of the relevant model (including fuzzy chance constrained confidence value and environmental risk threshold) is discussed. The results of multimodal transport path planning optimization are summarized. Change rule of parameter setting.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：U116.2
[Abstract]:The sustainable development of national economy and society needs the support of efficient freight transportation system.With the continuous improvement of China's comprehensive transportation system,as an advanced form of transport organization,multimodal transport has been greatly promoted and applied in transportation practice.The network of multimodal transport service is becoming more and more mature,and the economic and social benefits of transportation are becoming more and more mature. Efficient operation and management of the multimodal transport service network can not be separated from scientific and rational transport planning. In the three-tier planning system of the multimodal transport service network "strategy-tactics (network design) -operation", the route optimization at the operational level is directly oriented to the diversified transport needs of customers, and it is a multimodal transport service. It is of great significance and practical value to study the economic, timeliness and reliability of service network, and it is also one of the hot issues in the field of transportation planning. Based on the feasibility of decision support, this paper, from the perspective of system engineering, comprehensively considers the six planning features of optimization object, transportation service mode, network capability, commodity flow integrity, optimization criteria and solving methods, starts with the basic transport scenario modeling, and according to the nature of goods (conventional goods represented by ordinary containers). And the non-conventional goods represented by dangerous goods are subdivided into several parts, and the modeling of complex transportation scenarios and the design of exact solution strategies for multimodal transport path planning are further studied systematically. Six planning features of the route planning problem. Especially in view of the characteristics of "transportation service mode setting", this paper focuses on two types of transportation service modes based on the analysis of the multimodal transport service network system, i.e. the flexible operation service mode represented by highway transportation service and the open service mode represented by railway transportation service. The service mode of the train operation scheme is summarized, and the space-time constraints of the train operation scheme on the multimodal transport path planning are summarized. Thus, the transportation service mode setting in the optimization modeling is extended from the single transport service mode to the multi-transport service mode. This is also one of the important innovations of this paper. (2) In the optimization modeling, this paper first introduces the optimization model. This paper studies the optimization modeling of the basic problems of multimodal transport path planning under the assumptions of single commodity flow, single transportation service mode and single objective optimization. A 0-1 integer linear programming model is constructed. The model is applied to the sensitivity analysis of multimodal transport path planning to the changes of supply and demand. According to the quantitative calculation and analysis, it is helpful to supply and demand. Then, based on the "point-arc" modeling method of the basic transport scenario problem, this paper takes the two most representative types of goods, ordinary containers and dangerous goods, as the research object, considering the multi-commodity/dangerous goods flow planning, multi-transportation service mode setting and so on. Firstly, a mixed chance-constrained integer nonlinear programming model for routing problem of general container multimodal transport under complex transport scenarios is constructed with the objective of generalized cost optimization of multi-commodity flow. Then, Gaussian plume model and box model are used to analyze the social risk in multimodal transport service network. The environmental risk is analyzed and measured, and the "generalized cost-social risk" dual-objective mixed chance-constrained integer nonlinear programming model for the path planning problem of multimodal transport of dangerous goods with environmental risk threshold constraints is constructed. (3) In the design of solution methods and case optimization analysis, this paper focuses on the exact solution strategy. Design, that is to say, first identify the nonlinear part of the nonlinear programming model, then linearize the transformation, get the equivalent linear programming model, and finally use the classical exact solution algorithm (such as branch and bound method) in the mathematical programming software (such as LINGO) to solve the problem simulation. In this paper, the Pareto boundary of the bi-objective optimization problem is obtained by solving the bi-objective optimization problem with the strategy of linearization transformation of integrated model and standardized weighted summation. Finally, a large-scale example is given to verify the practical application of the optimization model and the exact solution strategy in two kinds of complex transportation scenario modeling problems. At the same time, sensitivity analysis method and fuzzy simulation method are used to analyze the feasibility of the problem, and the relationship between the optimal results of multimodal transport path planning and the parameters of the relevant model (including fuzzy chance constrained confidence value and environmental risk threshold) is discussed. The results of multimodal transport path planning optimization are summarized. Change rule of parameter setting.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：U116.2
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