鐵路集裝箱中心站物流系統(tǒng)資源調(diào)配優(yōu)化與仿真研究
發(fā)布時(shí)間：2019-03-27 21:31
【摘要】：集裝箱運(yùn)輸費(fèi)用低、效率高、協(xié)作性好,目前已受到各界的普遍重視。鐵路集裝箱運(yùn)輸作為其中一個(gè)關(guān)鍵環(huán)節(jié),在整個(gè)集裝箱運(yùn)輸系統(tǒng)中發(fā)揮著重要作用。鐵路集裝箱中心站是辦理貨物到發(fā)、存儲(chǔ)、加工等業(yè)務(wù)的主要場所,也是現(xiàn)代綜合物流體系中的重要組成部分。在日益激烈的市場競爭中,只有不斷提高作業(yè)效率、降低運(yùn)營成本,才能得以生存。然而,由于鐵路集裝箱中心站物流系統(tǒng)比較龐大,且具有高度非線性和動(dòng)態(tài)性的特點(diǎn),同時(shí)其作業(yè)過程影響因素眾多,各環(huán)節(jié)之間的邏輯比較復(fù)雜,因此對系統(tǒng)優(yōu)化的研究十分困難。本文對鐵路集裝箱中心站物流系統(tǒng)相關(guān)優(yōu)化問題分別進(jìn)行研究,采用不同的優(yōu)化方法,對系統(tǒng)各環(huán)節(jié)以及作業(yè)資源進(jìn)行分析和優(yōu)化,從而達(dá)到科學(xué)管理和控制的目的。狀態(tài)空間模型是在動(dòng)態(tài)系統(tǒng)符合馬爾科夫性假設(shè)基礎(chǔ)上,由平穩(wěn)時(shí)間序列分析而來的一種動(dòng)態(tài)時(shí)域模型,該模型不僅能夠準(zhǔn)確地描述系統(tǒng)內(nèi)部狀態(tài),而且能夠很好地闡釋內(nèi)部狀態(tài)與外部輸入、輸出變量的聯(lián)系�；バ畔⒓夹g(shù)是典型的特征選擇高維數(shù)據(jù)分離度量方法,通過建立高維特征提取向量與輸出分類信息之間的內(nèi)在聯(lián)系,達(dá)到原始高維特征空間降維的目的。本文利用狀態(tài)空間時(shí)間序列模型對于多輸入、輸出變量復(fù)雜問題的適用性,且不需要大量歷史數(shù)據(jù)對系統(tǒng)狀態(tài)進(jìn)行描述的特點(diǎn),建立了鐵路集裝箱中心站所在區(qū)域貨運(yùn)需求預(yù)測狀態(tài)空間時(shí)間序列模型。同時(shí),采用互信息技術(shù)對原始高維輸入數(shù)據(jù)進(jìn)行降維,并針對自然災(zāi)害、政策變動(dòng)等一些特殊影響因素,提出加權(quán)的互信息計(jì)算方法,以提高綜合信息提取與數(shù)據(jù)降維的能力。通過與LIBSVM支持向量回歸模型以及局部線性小波神經(jīng)網(wǎng)絡(luò)模型的對比實(shí)驗(yàn),證明了該模型對于小樣本、高維度區(qū)域貨運(yùn)需求預(yù)測問題的有效性。排隊(duì)論是研究系統(tǒng)運(yùn)作策略相關(guān)問題的一種有效方法,由該理論建立起來的模型可進(jìn)一步分為靜態(tài)排隊(duì)模型以及瞬時(shí)排隊(duì)模型。瞬時(shí)排隊(duì)模型由于系統(tǒng)狀態(tài)描述比較困難、計(jì)算相對復(fù)雜,因此其應(yīng)用受到許多限制。鐵路集裝箱中心站大門系統(tǒng)具有很強(qiáng)的動(dòng)態(tài)性,傳統(tǒng)靜態(tài)排隊(duì)模型難以對系統(tǒng)進(jìn)行準(zhǔn)確描述。本文針對鐵路集裝箱中心站大門系統(tǒng)擁塞問題,通過搜集有關(guān)數(shù)據(jù),統(tǒng)計(jì)得出外部卡車到達(dá)時(shí)間間隔以及大門系統(tǒng)服務(wù)時(shí)間分布規(guī)律,并在此基礎(chǔ)上分別建立瞬時(shí)排隊(duì)模型及系統(tǒng)優(yōu)化模型。采用等可能組合優(yōu)化求解方法對模型進(jìn)行求解計(jì)算。通過系統(tǒng)仿真對比實(shí)驗(yàn)以及三個(gè)方面的靈敏度分析,證明模型與方法的合理性及有效性。針對鐵路中心站起重機(jī)調(diào)度與箱位分配決策問題,本文在綜合考慮集裝箱堆存方向、軌道式集裝箱門式起重機(jī)安全距離等因素基礎(chǔ)上,以最大作業(yè)完成時(shí)間最小化為目標(biāo),建立數(shù)學(xué)模型。啟發(fā)式算法作為非確定性多項(xiàng)式完全問題近似求解的重要方法,在解決鐵路集裝箱中心站有關(guān)優(yōu)化問題方面起著十分重要作用�；厮菟阉鲀�(yōu)化算法是目前較新的一種進(jìn)化算法,由于其總體結(jié)構(gòu)比較簡單,因此能夠更加快速、有效地求解高維多模優(yōu)化模型。同時(shí),為了進(jìn)一步提高算法尋找最優(yōu)解的能力,并解決該算法易陷入局部最優(yōu)解的缺點(diǎn),本文對回溯搜索優(yōu)化算法進(jìn)行了相應(yīng)的改進(jìn),從而提高算法的性能以及對于該問題的適應(yīng)度。通過數(shù)值算例分析,證明鐵路中心站起重機(jī)調(diào)度與箱位分配模型及改進(jìn)回溯搜索優(yōu)化算法對于求解該問題的可行性及有效性。鐵路集裝箱中心站物流系統(tǒng)很難采用傳統(tǒng)數(shù)學(xué)模型予以描述,因此系統(tǒng)仿真方法是解決此類問題的有效途徑。Simio仿真軟件是面向“智能對象”的新一代三維系統(tǒng)仿真軟件,采用獨(dú)特的三層結(jié)構(gòu),對系統(tǒng)對象的行為、屬性以及過程進(jìn)行定義,因此具有良好的離散系統(tǒng)仿真能力。本文根據(jù)鐵路集裝箱中心站物流系統(tǒng)整體作業(yè)流程,建立相應(yīng)的Simio系統(tǒng)仿真模型,通過系統(tǒng)實(shí)際參數(shù)輸入,模擬特定條件下系統(tǒng)的運(yùn)作情況。改變系統(tǒng)相關(guān)影響因素以及資源配置數(shù)量分別進(jìn)行多次仿真實(shí)驗(yàn),觀察結(jié)果變化并得出相應(yīng)結(jié)論。提出鐵路集裝箱中心站物流系統(tǒng)資源配置優(yōu)化計(jì)算方法,并嵌入系統(tǒng)仿真邏輯,在仿真模型運(yùn)行的過程中計(jì)算系統(tǒng)最優(yōu)的資源數(shù)量。由模型實(shí)驗(yàn)結(jié)果可以得出,系統(tǒng)仿真方法能夠?qū)﹁F路集裝箱中心站物流系統(tǒng)進(jìn)行有效的模擬和監(jiān)控,其仿真優(yōu)化結(jié)果有助于管理者實(shí)施相關(guān)決策。本文采用互信息技術(shù)、狀態(tài)空間時(shí)間序列、等可能組合算法、改進(jìn)回溯搜索算法,以及Simio系統(tǒng)仿真技術(shù)對鐵路集裝箱中心站物流系統(tǒng)進(jìn)行研究,從區(qū)域貨運(yùn)需求預(yù)測、大門系統(tǒng)擁塞優(yōu)化、起重機(jī)調(diào)度與箱位分配決策、系統(tǒng)資源優(yōu)化配置方面實(shí)現(xiàn)系統(tǒng)的智能控制。本文的研究具有重要的理論意義和實(shí)際應(yīng)用價(jià)值,并為今后的研究奠定了基礎(chǔ)。
[Abstract]:The cost of container transportation is low, the efficiency is high, the cooperation is good, and it is now widely regarded by various circles. As one of the key links, railway container transport plays an important role in the whole container transportation system. The railway container central station is the main place for handling the goods, storage and processing, and it is also an important part of the modern integrated logistics system. In the increasingly fierce market competition, only the operation efficiency is continuously improved, the operation cost is reduced, and the survival can be realized. However, because the logistics system of the railway container central station is relatively large, and has the characteristics of high nonlinearity and dynamics, and the influence factors of the operation process are numerous, the logic between the various links is more complex, and therefore, the research on the system optimization is very difficult. In this paper, the optimization problems related to the logistics system of the railway container central station are studied respectively, and different optimization methods are adopted to analyze and optimize the links and operating resources of the system, so as to achieve the purpose of scientific management and control. The state space model is a dynamic time-domain model which is analyzed by the stationary time series on the basis of the Markov-based hypothesis of the dynamic system. The model not only can accurately describe the internal state of the system, but also can well explain the internal state and the external input. The contact of the output variable. The mutual information technology is a typical feature selection high-dimensional data separation measurement method, and the purpose of reducing the dimension of the original high-dimensional feature space is achieved by establishing the internal relation between the high-dimensional feature extraction vector and the output classification information. In this paper, the applicability of the state space time series model to the complex problem of multi-input and output variables is used, and a large amount of historical data is not required to describe the system state, and the space time series model of the freight demand forecast state in the region where the railway container central station is located is established. At the same time, using the mutual information technology to dimension the original high-dimensional input data, and aiming at some special influence factors such as natural disaster and policy change, a weighted mutual information calculation method is proposed to improve the ability of comprehensive information extraction and data reduction. Based on the comparison between the support vector regression model of the LIBSVM and the local linear wavelet neural network model, the validity of this model for small samples and high-dimension freight demand forecasting is proved. The queuing theory is an effective method for studying the operation strategy of the system. The model established by the theory can be further divided into the static queuing model and the instantaneous queuing model. The instantaneous queuing model is relatively complicated because the system state description is difficult and the calculation is relatively complex, so its application is limited. The gate system of the railway container central station has a strong dynamic, and the traditional static queuing model is difficult to accurately describe the system. Aiming at the problem of the congestion of the gate system of the railway container central station, by collecting the relevant data, the time interval of the arrival time of the external truck and the time distribution of the service time of the gate system are obtained, and the instantaneous queuing model and the system optimization model are set up on the basis of this. The method is used to calculate the model by using the possible combination optimization solution method. The rationality and validity of the model and method are proved through the system simulation and contrast experiment and the sensitivity analysis of the three aspects. In order to solve the problem of scheduling and distribution of the crane in the central station of the railway, this paper, based on the consideration of the factors such as the stacking direction of the container, the safe distance of the rail-type container gantry crane, minimizes the time of the maximum operation, and sets up a mathematical model. The heuristic algorithm is an important method for solving the problem of the complete problem of the non-deterministic polynomial, and plays an important role in solving the problem of the optimization of the railway container central station. The backtracking search optimization algorithm is a new evolutionary algorithm, because the overall structure is relatively simple, so the high-dimensional multi-mode optimization model can be solved more quickly and effectively. At the same time, in order to further improve the ability of the algorithm to find the optimal solution, and to solve the disadvantage that the algorithm is easy to fall into the local optimal solution, this paper makes a corresponding improvement to the backtracking search optimization algorithm, so as to improve the performance of the algorithm and the fitness of the problem. By means of numerical examples, it is proved that the scheduling and box-level allocation model of the railway central station and the improved backtracking search optimization algorithm are feasible and effective to solve the problem. It is difficult to describe the traditional mathematical model in the logistics system of the railway container central station, so the system simulation method is an effective way to solve such problems. Simo simulation software is a new-generation three-dimensional system simulation software facing the "Smart Objects", and adopts a unique three-layer structure, and defines the behavior, the property and the process of the system object, thus having good discrete system simulation capability. According to the overall operation process of the logistics system of the railway container central station, this paper establishes the corresponding Simio system simulation model, and simulates the operation of the system under specific conditions through the system's actual parameter input. The influence factors of the system and the number of resource allocation are simulated, and the results are changed and the corresponding conclusions are obtained. The method for optimizing the resource allocation of the logistics system of the railway container central station is put forward, and the simulation logic of the system is embedded, and the optimal resource quantity of the system is calculated in the process of running the simulation model. The result of the model experiment can be obtained, and the system simulation method can effectively simulate and monitor the logistics system of the railway container central station, and the simulation optimization result can help the manager to implement the relevant decision. in this paper, we use cross-information technology, state space time series, and other possible combination algorithms, improve the backtracking search algorithm, and Simio system simulation technology to study the logistics system of the railway container central station, from the regional freight demand forecast, the gate system congestion optimization, The intelligent control of the system is realized in the aspects of the scheduling of the crane and the decision of the allocation of the box position and the optimal configuration of the system resources. The research of this paper has important theoretical and practical value, and lays the foundation for future research.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：U294.3
本文編號(hào)：2448580
[Abstract]:The cost of container transportation is low, the efficiency is high, the cooperation is good, and it is now widely regarded by various circles. As one of the key links, railway container transport plays an important role in the whole container transportation system. The railway container central station is the main place for handling the goods, storage and processing, and it is also an important part of the modern integrated logistics system. In the increasingly fierce market competition, only the operation efficiency is continuously improved, the operation cost is reduced, and the survival can be realized. However, because the logistics system of the railway container central station is relatively large, and has the characteristics of high nonlinearity and dynamics, and the influence factors of the operation process are numerous, the logic between the various links is more complex, and therefore, the research on the system optimization is very difficult. In this paper, the optimization problems related to the logistics system of the railway container central station are studied respectively, and different optimization methods are adopted to analyze and optimize the links and operating resources of the system, so as to achieve the purpose of scientific management and control. The state space model is a dynamic time-domain model which is analyzed by the stationary time series on the basis of the Markov-based hypothesis of the dynamic system. The model not only can accurately describe the internal state of the system, but also can well explain the internal state and the external input. The contact of the output variable. The mutual information technology is a typical feature selection high-dimensional data separation measurement method, and the purpose of reducing the dimension of the original high-dimensional feature space is achieved by establishing the internal relation between the high-dimensional feature extraction vector and the output classification information. In this paper, the applicability of the state space time series model to the complex problem of multi-input and output variables is used, and a large amount of historical data is not required to describe the system state, and the space time series model of the freight demand forecast state in the region where the railway container central station is located is established. At the same time, using the mutual information technology to dimension the original high-dimensional input data, and aiming at some special influence factors such as natural disaster and policy change, a weighted mutual information calculation method is proposed to improve the ability of comprehensive information extraction and data reduction. Based on the comparison between the support vector regression model of the LIBSVM and the local linear wavelet neural network model, the validity of this model for small samples and high-dimension freight demand forecasting is proved. The queuing theory is an effective method for studying the operation strategy of the system. The model established by the theory can be further divided into the static queuing model and the instantaneous queuing model. The instantaneous queuing model is relatively complicated because the system state description is difficult and the calculation is relatively complex, so its application is limited. The gate system of the railway container central station has a strong dynamic, and the traditional static queuing model is difficult to accurately describe the system. Aiming at the problem of the congestion of the gate system of the railway container central station, by collecting the relevant data, the time interval of the arrival time of the external truck and the time distribution of the service time of the gate system are obtained, and the instantaneous queuing model and the system optimization model are set up on the basis of this. The method is used to calculate the model by using the possible combination optimization solution method. The rationality and validity of the model and method are proved through the system simulation and contrast experiment and the sensitivity analysis of the three aspects. In order to solve the problem of scheduling and distribution of the crane in the central station of the railway, this paper, based on the consideration of the factors such as the stacking direction of the container, the safe distance of the rail-type container gantry crane, minimizes the time of the maximum operation, and sets up a mathematical model. The heuristic algorithm is an important method for solving the problem of the complete problem of the non-deterministic polynomial, and plays an important role in solving the problem of the optimization of the railway container central station. The backtracking search optimization algorithm is a new evolutionary algorithm, because the overall structure is relatively simple, so the high-dimensional multi-mode optimization model can be solved more quickly and effectively. At the same time, in order to further improve the ability of the algorithm to find the optimal solution, and to solve the disadvantage that the algorithm is easy to fall into the local optimal solution, this paper makes a corresponding improvement to the backtracking search optimization algorithm, so as to improve the performance of the algorithm and the fitness of the problem. By means of numerical examples, it is proved that the scheduling and box-level allocation model of the railway central station and the improved backtracking search optimization algorithm are feasible and effective to solve the problem. It is difficult to describe the traditional mathematical model in the logistics system of the railway container central station, so the system simulation method is an effective way to solve such problems. Simo simulation software is a new-generation three-dimensional system simulation software facing the "Smart Objects", and adopts a unique three-layer structure, and defines the behavior, the property and the process of the system object, thus having good discrete system simulation capability. According to the overall operation process of the logistics system of the railway container central station, this paper establishes the corresponding Simio system simulation model, and simulates the operation of the system under specific conditions through the system's actual parameter input. The influence factors of the system and the number of resource allocation are simulated, and the results are changed and the corresponding conclusions are obtained. The method for optimizing the resource allocation of the logistics system of the railway container central station is put forward, and the simulation logic of the system is embedded, and the optimal resource quantity of the system is calculated in the process of running the simulation model. The result of the model experiment can be obtained, and the system simulation method can effectively simulate and monitor the logistics system of the railway container central station, and the simulation optimization result can help the manager to implement the relevant decision. in this paper, we use cross-information technology, state space time series, and other possible combination algorithms, improve the backtracking search algorithm, and Simio system simulation technology to study the logistics system of the railway container central station, from the regional freight demand forecast, the gate system congestion optimization, The intelligent control of the system is realized in the aspects of the scheduling of the crane and the decision of the allocation of the box position and the optimal configuration of the system resources. The research of this paper has important theoretical and practical value, and lays the foundation for future research.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：U294.3
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2 李國亮;基于改進(jìn)遺傳算法的加工中心生產(chǎn)車間物流改善研究[D];沈陽工業(yè)大學(xué);2013年
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