遺伝的アルゴリズムの改良に基づくマルチターゲットの運輸問題に関する研究
| العنوان: | 遺伝的アルゴリズムの改良に基づくマルチターゲットの運輸問題に関する研究 |
|---|---|
| المؤلفون: | LI, Jiacheng |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | heterogeneous vehicles, game theory, fatigue driving, genetic algorithm, information entropy, crowdsourcing distribution, multimodal transport |
| الوصف: | With the rapid development of economic globalization and information technology, rapid changes have taken place in all fields of society. The status of modern logistics industry in the process of the flow of social means of production and commodities has become increasingly prominent, accompanied by profound changes in production and manufacturing, material circulation, commodity transactions and management methods. Logistics cost accounts for a large share of national GDP, which can reflect the quality and scale of a country's national economy, reduce the logistics cost of enterprises, and greatly improve the profit space. Especially under the background of economic globalization, the competition among enterprises is increasingly fierce, and the impact of logistics on the competitiveness of enterprises is increasingly obvious. In the modern e-commerce environment, with the rapid development of science and technology, the space for enterprises to obtain profits from the products themselves has been greatly reduced. In order to reduce costs and improve profits as much as possible, enterprises focus on logistics. In the whole logistics system, transportation is a very important link. Therefore, efforts to reduce the cost of logistics and transportation can greatly reduce the cost of the entire logistics system. This paper starts from the main factors involved in the transportation logistics, optimizes the main factors affecting the logistics, reduces costs and improves profits.Firstly, this paper discusses and studies the distribution personnel, mainly including the logistics distribution under the limitation of personnel fatigue and the delivery distribution mode under the new mode of personnel allocation - "crowdsourcing logistics". Aiming at the research on the limitation of fatigue, aiming at the maximization of customer satisfaction and the minimization of total cost, this paper constructs a model of path optimization for driver's fatigue driving, and designs a single Partheno-genetic algorithm for the model, which is verified by the distribution case of Japan's otaku. On the research of crowdsourcing delivery, taking the delivery network as the research object, this paper analyzes the distribution process, mode and existing problems of crowdsourcing delivery mode. Based on the purpose of optimizing the distribution network, taking the shortest distribution path and the least time delay as the objective function, the basic optimization model and dynamic optimization model of crowdsourcing distribution path with time window are established, and the rationality of the model is evaluated. Secondly, from the perspective of vehicle research and analysis, mainly study the two-tier node logistics distribution mode based on heterogeneous vehicles. This paper analyzes the common transportation vehicle selection problem in the existing transportation. Based on the genetic algorithm, taking the transportation cost of the double-layer logistics node of a city's seafood products as the optimization goal, and comprehensively considering the problem of taking delivery vehicle route and vehicle configuration strategy of different routes at the same time, the mathematical model of vehicle scheduling and transportation route problem in the double-layer node transportation route is established. In this paper, MATLAB software is used to solve the model based on traditional genetic algorithm and Partheno-genetic algorithm, and the correctness and effectiveness of the model and Partheno-genetic algorithm are verified.Then, from the perspective of transportation path mode, the research mainly involves the current hot "multimodal transport" problem. In this paper, the coal transportation in a country is taken as the research object. Under the mode of "iron water combined transportation", how to reasonably distribute the transportation capacity and correctly select the transportation mode can realize the enterprise to control the logistics cost and ensure the maximum profit. At the same time, based on the traditional genetic algorithm mechanism, aiming at the premature and local search ability of the traditional genetic algorithm in solving the logistics transportation path optimization problem are analyzed Due to the shortage of power, a hybrid genetic algorithm is proposed to solve the model.Finally, the optimization algorithm of logistics distribution is discussed. This paper presents a hybrid genetic algorithm based on information entropy and game theory. First, the initial population is generated by calculating population diversity with information entropy. Combined with parallel genetic algorithm, standard genetic algorithm (SGA), Partheno-genetic algorithm (PGA) and hybrid genetic algorithm (sga-pga) which integrates standard genetic algorithm and Partheno-genetic algorithm (sga-pga) are used to perform evolutionary operations. At the parallel node, information entropy and fitness value of each sub population are used Finally, three programs checking functions Rosenbrock function, Rastrigin function and Schaffer function are introduced to analyze the performance superiority of the algorithm. |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=jairo_______::13b8d8a5aa98804c6dead8be43306649 http://hdl.handle.net/10114/00022973 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.jairo.........13b8d8a5aa98804c6dead8be43306649 |
| قاعدة البيانات: | OpenAIRE |
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In the whole logistics system, transportation is a very important link. Therefore, efforts to reduce the cost of logistics and transportation can greatly reduce the cost of the entire logistics system. This paper starts from the main factors involved in the transportation logistics, optimizes the main factors affecting the logistics, reduces costs and improves profits.Firstly, this paper discusses and studies the distribution personnel, mainly including the logistics distribution under the limitation of personnel fatigue and the delivery distribution mode under the new mode of personnel allocation - "crowdsourcing logistics". Aiming at the research on the limitation of fatigue, aiming at the maximization of customer satisfaction and the minimization of total cost, this paper constructs a model of path optimization for driver's fatigue driving, and designs a single Partheno-genetic algorithm for the model, which is verified by the distribution case of Japan's otaku. On the research of crowdsourcing delivery, taking the delivery network as the research object, this paper analyzes the distribution process, mode and existing problems of crowdsourcing delivery mode. Based on the purpose of optimizing the distribution network, taking the shortest distribution path and the least time delay as the objective function, the basic optimization model and dynamic optimization model of crowdsourcing distribution path with time window are established, and the rationality of the model is evaluated.<br />Secondly, from the perspective of vehicle research and analysis, mainly study the two-tier node logistics distribution mode based on heterogeneous vehicles. This paper analyzes the common transportation vehicle selection problem in the existing transportation. Based on the genetic algorithm, taking the transportation cost of the double-layer logistics node of a city's seafood products as the optimization goal, and comprehensively considering the problem of taking delivery vehicle route and vehicle configuration strategy of different routes at the same time, the mathematical model of vehicle scheduling and transportation route problem in the double-layer node transportation route is established. In this paper, MATLAB software is used to solve the model based on traditional genetic algorithm and Partheno-genetic algorithm, and the correctness and effectiveness of the model and Partheno-genetic algorithm are verified.Then, from the perspective of transportation path mode, the research mainly involves the current hot "multimodal transport" problem. In this paper, the coal transportation in a country is taken as the research object. Under the mode of "iron water combined transportation", how to reasonably distribute the transportation capacity and correctly select the transportation mode can realize the enterprise to control the logistics cost and ensure the maximum profit. At the same time, based on the traditional genetic algorithm mechanism, aiming at the premature and local search ability of the traditional genetic algorithm in solving the logistics transportation path optimization problem are analyzed Due to the shortage of power, a hybrid genetic algorithm is proposed to solve the model.Finally, the optimization algorithm of logistics distribution is discussed. This paper presents a hybrid genetic algorithm based on information entropy and game theory. First, the initial population is generated by calculating population diversity with information entropy. Combined with parallel genetic algorithm, standard genetic algorithm (SGA), Partheno-genetic algorithm (PGA) and hybrid genetic algorithm (sga-pga) which integrates standard genetic algorithm and Partheno-genetic algorithm (sga-pga) are used to perform evolutionary operations. 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