Optimal Transportation Routes Research Articles

On Prospects of Analytic Hierarchy Process Application for Freight Transportation Safety Management in Integrated Transport Systems

Integrated transport systems are a perfect form of transportation organization, because they allow integrated use of competing modes of transport, providing a high level of transportation service at affordable prices and savings in transportation costs. With the increasing demand for such transportation, the issue of transport safety assessment is becoming more important, particularly in preservation of cargo and vehicles in each section of the transportation process. In the process of technical progress, it becomes increasingly difficult to achieve a high enough level of transport safety, which allows to ensure national security and interests in the field of transport activities. Unfortunately, transport safety management today is mainly carried out at organizational level, which needs to be supplemented with safety assessment of transport system’s objects. The development of methods for transport safety assessment remains a complex scientific task, the solving of which depends on the economic efficiency and safety of the transportation process. Since transport safety is the state of the transport system, its assessment includes the safety assessments of various transport infrastructures. Thus, there is some imaginary protection field of the object of transport infrastructure, which provides counteraction to a set of existing or perceived threats. The proposed algorithm for safe freight transportation routes development may be divided into two cyclical stages: optimal transport hub determination from the alternatives; optimal transportation route choosing between selected transport hubs. The method provides a comprehensive and rational framework for structuring a decision problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. The practical use of the proposed approach allows at the designing stage of multimodal transportation routes to evaluate their alternatives, according to the selected criteria and take the necessary measures in order to improve transport safety.

Finding Optimal Transport Route and Retail Outlet Location Using Mobile Phone Location Data

People are leaving their digital footprint everywhere as they move from one cell tower coverage to another in terms of Call Detail Records (CDR). This huge and variant data can be analyzed to find interesting human mobility patterns for socio-economic development and allow a city administrator to understand the daily commuting patterns of the city dwellers in almost real-time. This paper proposes the techniques and algorithms that use these data to identify (i) optimal transport routes in a city; (ii) Business viable retail outlet location in a city. The aggregated information has been modeled as a network, and graph-theoretic approaches are used to derive a feasible solution. The main advantage of this work is that CDR provides low cost, real-time, noise-free data that captures the evolving dynamics of the movement patterns, and hence any decision taken based on this will be apt and prompt.The only limitation of this study is the unavailability of raw CDR data due to the confidentiality issue for experimental proof of the proposed methods on a real city topology.

THE USING OF OPERATIONS RESEARCH METHODS TO OPTIMIZE FREIGHT ROAD TRANSPORTATION IN THE AGROINDUSTRIAL COMPLEX

An optimization model has been developed using linear programming and network analysis methods to determine the route of trucks for the transportation of homogeneous mass cargo. The study was carried out by means of economic and mathematical modelling of flows of a homogeneous mass cargo between a supplier and several consumers (using the example of transporting solid organic fertilizers from a storage facility to crop rotation fields and between them). It has been established that the volume of road transport of organic fertilizers for delivery from storage sites to crop rotation fields in agricultural regions of the country is very large. In agricultural production, the process of determining the optimal transportation route, including large volumes of fertilizers, is very laborious and complex in terms of organization, material, financial, and labour costs. The costs associated with transporting such a quantity of fertilizers is very high, which necessitates the optimization of this process. The study of generalized flow problems in a network setting was carried out on the example of road transport of solid organic fertilizers to crop rotation fields using the methods of operations research. It is possible to optimize the parameters of this transport process by developing its model using the methods of linear programming and network analysis and performing calculations on it. The route of transportation, in which the total costs of road transportation will be minimal, will be optimal for the considered transport process. The criterion for the effectiveness of the choice (the objective function of the mathematical model) is the total costs of transporting a given volume of cargo from the supplier to several consumers, subject to their minimization. The factors that determine these costs are highlighted and calculated dependencies are developed to determine them. A comprehensive method for optimizing the technology of transporting organic fertilizers by road on farms has been further developed. The developed model can be used by enterprises-suppliers of road transport services, farms, to increase the volume and improve the efficiency of road transport of fertilizers and other bulk cargo. It seems promising to develop an algorithm and a program for this model to determine the optimal route of movement of vehicles for the distribution of a given volume of cargo

Optimization of New Energy Public Transportation Network Based on Ant Colony Algorithm and Low-Carbon Concept

In order to solve the optimization of new energy bus line network, a new energy bus line network based on ant colony algorithm and low-carbon concept is proposed. Firstly, the model of public transport network is established combined with OD matrix, and the improved ant colony algorithm is used to iteratively optimize the initial suboptimal route set, optimize the objective function, and finally obtain the optimal public transport route set. Secondly, the improved ant colony algorithm based on simulated annealing solves the design of public transport network, and the optimization scheme greatly reduces the number of passenger transfers and the total travel time of passengers. Finally, simulated annealing algorithm, basic ant colony algorithm, and simulated annealing improved ant colony algorithm are used to optimize the objective function. It is proved that the improved ant colony algorithm of simulated annealing can find the optimal solution of the three algorithms when solving the problem of public transport network design, which is better than the solution of basic ant colony and simulated annealing algorithm. The solution efficiency is 10.6 times that of simulated annealing algorithm and 3.5 times that of basic ant colony algorithm.

Optimization of Urban Waste Transportation Route Based on Genetic Algorithm

Under the normal conditions of the new economy, people’s living standards have improved; the amount of urban domestic waste has increased suddenly; and the differentiation of waste has become more and more complicated. However, the garbage transportation method at this stage has been difficult to meet the needs of reality. Therefore, it is particularly urgent to reform the original and simple treatment methods and adopt the latest and more reasonable garbage transportation. The urban waste transportation route optimization described in this article is quite complicated in the specific problems faced in the optimization of the urban domestic waste transportation route. This paper proposes to combine computer science to study the system optimization model and combine information management and other disciplines to develop and apply research on the dynamic management software of urban waste logistics systems. In the modern service industry, logistics occupies an important position. The optimization of urban waste transportation routes based on genetic algorithms also promotes the development of high-end modern service industries and is an important task to promote urban development and maintained hygiene and improve the healthcare of the citizens. The optimization of urban waste transportation routes is conducive to creating a clean and tidy urban environment.

Routes Choice in the International Intermodal Networks under the Soft Time Window

There are many transportation nodes in multimodal transport. It is more in line with the actual transportation situation to reasonably select the transportation mode from the perspective of the elastic constraint of arrival time. Considering the elastic constraint of arrival time, the soft time window factor is brought into the research of multimodal transport route optimization, the route optimization model is established, and the appropriate genetic algorithm is selected and designed to deal with it. So as to obtain the optimal transportation scheme of multimodal transport, multimodal transport system optimization involves many factors such as multimodal transport organization, policy, process, responsibility, coordination, and environment.

Research on Optimizing Multimodal Transport Path under the Schedule Limitation Based on Genetic Algorithm

Abstract Multimodal transportation is getting more and more attention due to its economical and efficient characteristics. Choosing a reasonable transportation plan can effectively control transportation costs. Considering that there are fixed schedules for railway and waterway transportation in real life, this article will establish a multimodal transportation route optimization model with the goal of minimizing the total transportation cost consisting of transportation cost, transit cost, waiting cost and carbon emission cost. The genetic algorithm based on preservation strategy and immigration strategy is used to solve the model. The effectiveness of the model is proved by the case study, and it can provide decision support for the choice of multimodal transportation scheme.

Optimization of Waste Transportation Routes using Multi-objective Non-dominated Sorting Genetic Algorithm II (MNSGA-II) in the Eastern and Southern Regions of Bandung City, Indonesia

Ensuring high-quality and effective urban waste management has been an important priority to achieve sustainable and environmental-friendly cities and communities mandated by Sustainable Development Goals (SDGs). The massively growing population in urban regions of developing countries, such as Bandung City, Indonesia, leads to the increasing volume of daily goods consumption and households waste production. The waste transportation route is one of the main determining factors for the cost of waste management. In this paper, we introduce the Multi-objective Non-dominated Sorting Genetic Algorithm II (MNSGA-II) to solve the waste transportation route optimization problem in the Eastern and Southern Regions of Bandung City, Indonesia. Compared to the existing traditional evolutionary algorithms, MNSGA-II offers three major important benefits: efficient computational complexity, no requirement of sharing parameters, and a non-elitism mechanism. Algorithm parameters include the number of generations, mutation rate, and crossover rate. Our extensive experiments suggest the best solution resulted in 14 routes with a total distance of 152,63 km. Further, our proposed route optimization is potentially beneficial to support the improvement of the sustainable waste management service system at Bandung City.

Modern Trends in Artificial Intelligence in the Transport System

The article presents the results of a study of the spheres of activity of the most active use of artificial intelligence technologies. The clear advantages and attractiveness of artificial intelligence technologies for the competitive advantage of companies in various fields of activity are considered. A classification of artificial intelligence technologies in business is proposed. The types of technologies are grouped according to their belonging to the technologies of machine, deep learning, neural networks, natural language processing, expert systems, robotization of automated systems. From the standpoint of the classification of artificial intelligence technologies, forecasts of leading experts and auditors of the use of artificial intelligence are analyzed: Price Waterhouse Coopers, McKinsey Institute, Gartner, New Vantage Partners. The authors’ attention is focused on the problems of using artificial intelligence for effective traffic management. Such aspects of this problem are considered as increasing the degree of uniformity of traffic flow, optimization of public transport routes, the need to install special equipment on vehicles, such as sensors, sensors, information boards for collecting and subsequent processing of information; lighting control systems for transport highways; means of road control. The prospects for the development of intelligent transport systems in Moscow and St. Petersburg, the Leningrad region are analyzed.

Research on long-distance cold chain logistics route optimization considering transport vibration and refrigerant carbon emission

The long-distance cold chain transportation of fresh products from the place of origin to sale is costly due to the high probability of spoilage and high carbon emissions. The potential factors for the high cost of long-distance cold chain transportation are the spoilage of fresh goods caused by transportation vibration and the carbon emission caused by refrigerant use. How to minimize the impact of these factors through optimal transportation route planning is the current problem to be solved. Firstly, a longdistance cold chain logistics route planning model including goods spoilage cost and carbon emission cost is developed, considering the goods spoilage cost caused by transportation vibration and the carbon emission cost generated by refrigerant as well as several other factors. Secondly, an improved ant colony algorithm is used to solve the optimal solution of the model, and the algorithm is redesigned for the characteristics of the model. Thirdly, the pheromone update mechanism in the ant colony algorithm is improved by adding pheromone coefficients to accelerate the convergence speed of the algorithm. Finally, the validity of the model is verified by an arithmetic example. The model and method proposed in this paper help to reduce the cost in the process of long-distance cold chain transportation and bring practical application value.

The Optimal Route Selection Model of Fresh Agricultural Products Transportation Based on Bee Colony Algorithm

In order to optimize the distribution route of fresh agricultural products and reduce the distribution cost, the optimal route selection model of fresh agricultural products transportation based on bee colony algorithm is constructed. After establishing the transportation road network model of fresh agricultural products and analyzing the transportation road information, the transportation road network zoning is realized by the dynamic zoning method of transportation road network based on spectral clustering algorithm, taking the unblocked area and congested area as the zoning purpose. Based on the traffic zoning information, the transportation route optimization model of fresh agricultural products with time window is constructed. Solved by bee colony algorithm to obtain the distribution route of fresh agricultural products with the lowest distribution cost and the highest customer satisfaction. The experimental results show that the model can choose the fresh agricultural products distribution route with the lowest distribution cost and the highest customer satisfaction under the two working conditions of smooth traffic and congestion.

Minimum cost lexicographic evacuation flow finding in intuitionistic fuzzy networks

Nowadays, various emergencies that are human-made or natural occur widely and threaten people’ lives and health. One of the most important evacuation tasks is the minimum cost lexicographic flow modelling task, which allows aggrieved to be transported to safe areas along the optimal transportation routes, taking into account the priority of shelters. It is inevitable that when modelling an evacuation scenario, an expert will encounter difficulties in setting network parameters due to the inherent uncertainty of a network, the rapid change in the nature of the movement, etc. Intuitionistic fuzzy sets allow simulating doubts and uncertainty of a decision-maker when choosing a membership function. Due to the increasing complexity of the decision-making problems, experts cannot assess all the network parameters correctly because much specific knowledge is required, and each expert cannot be familiar with all attributes equally. Therefore, different decision-makers should have different values for various attributes. The algorithm proposed incorporates the search for the order of reliable shelters according to the modified TOPSIS method and the minimum cost paths in intuitionistic fuzzy conditions based on the non-standard subtraction operation. A case study is conducted to verify the proposed algorithm.

Study on Cold Chain Transportation Model of Fruit and Vegetable Fresh-Keeping in Low-Temperature Cold Storage Environment

Due to the limitation of later stage intelligent algorithms, the fruit and vegetable fresh-keeping cold chain transportation scheme did not meet the expectation and could not achieve the dual objectives of the shortest time and the lowest consumption at the same time. In order to solve the above problems, a cold chain transportation model of fruit and vegetable fresh-keeping in a low-temperature cold storage environment is proposed. The model is based on the topology of the cold chain transportation network. By setting the assumptions of the fruit and vegetable fresh-keeping cold chain transportation model, the objective model is composed of three parts: vehicle power fuel consumption cost, cold chain transportation refrigeration cost, and total fruit and vegetable loss cost. Under six constraints, the improved ant colony algorithm is used to find the optimal fruit and vegetable fresh-keeping cold chain transportation route. The experimental results show that compared with the methods based on ALNS, genetic algorithm, and quantum bacterial foraging optimization algorithm, the research method can bring the best comprehensive benefit by accomplishing the fruit and vegetable transportation task in the shortest time at the lowest cost, and the research goal is thus achieved.

Risk-informed based comprehensive path-planning method for radioactive materials road transportation

The optimization of transportation routes of radioactive materials (RADMAT) is recognized as one of the most important measures to reduce the radioactive risks and costs during transportation. However, the route optimization indicators have not been fully considered and quantified in current researches. Here, we propose a Risk-Informed based Comprehensive Path-Planning method (RICPP) for RADMAT Road Transportation (RMRT) route optimization by considering radiological risk cost, time cost, and economical cost. Among which, the ET/FT based Probabilistic Safety Assessment (PSA) model is established to quantitatively assess the accident occurrence probability, and then the PEHR (personnel, environment, hazard target, and rescue force) comprehensive severity indexes considering vulnerability and resilience are established and quantified to characterize the accident radiological consequence. Finally, the gray relation analysis (GRA) model is employed to select an optimal path considering the multi-objective route planning indicators. The case study results show that the obtained path could reasonably reduce risks and costs during the transportation process, which demonstrates the effectiveness of the proposed method. The proposed RICPP methodology is beneficial for selecting a safer and more economical route for radioactive materials road transportation.

Green Logistics Practices Seeking Development of Sustainability: Evidence from Lithuanian Transportation and Logistics Companies

Reducing the harmful effects on the environment and increasing the expression of sustainable development principles is one of the most topical challenges all around the world. Given the importance of logistics for the economy and the growing concern for the environment, the purpose of this article was to reveal a green logistics (GL) practice framework for sustainable development. Based on a systematic and comparative analysis of the scientific literature, the authors present a theoretical conceptual model for applying GL practices to sustainable development. In order to assess the expression of GL practices and their determinants in Lithuanian transport and logistics services companies, a quantitative questionnaire survey was conducted. Descriptive statistics, correlation, and regression analyses were used to analyze the data. The results made it possible to identify GL areas such as green transportation, green warehousing, green management, sustainable waste management, and the prevailing GL practices in Lithuania: “Eco-driving”, “Optimization of transport routes”, and “Optimization of transport cargo distribution”. The factors that most encouraged the application of GL practices in the studied companies were: legal regulation and policies, requirements of business partners, service users, customers and society, awareness of the company’s top management, and corporate culture focused on environmental conservation and sustainable development.

Transportation route optimization based on heuristic algorithm

With the rapid development of Internet technology, many enterprises are committed to finding the best solution in transportation organization and solving the vehicle distribution routing problem. Firstly, this paper introduces the current situation of transportation organization of Sichuan Yida Feiniu Transportation Company, and analyzes the main problems of the company. Secondly, through the prediction of freight volume, prepare the truck vehicle operation plan and optimize the company’s transportation organization and production plan. Finally, the heuristic algorithm is used to establish a mixed integer programming mathematical model to optimize the pooled vehicle distribution path problem and the vehicle distribution path with time window. In terms of centralized vehicle distribution, combined with the actual situation of Sichuan Yida Feiniu Transportation Company, an example is analyzed, the shortest total path is obtained, and the goal of shortest vehicle travel distance is realized. Through the optimization of the company’s transportation organization, this paper is of great significance to improve the company’s transportation organization to a certain extent.

Study on the strategy of multimodal transportation of medical aid materials for public health emergencies: a case study basing on COVID-19

The emergency response to sudden public health incident often encounters problems such as the long distance between the medical material supply node and the demand point or the destruction of key roads, which makes it difficult to transport materials directly to the disaster area by vehicles in time. Helicopters are increasingly being used to transport critical medical emergency resources, but it is not easy to distribute medical supplies through helicopter in large-scale public health incidents. In order to solve the above problems, a two-stage combined transportation method for medical supplies based on clustering is proposed in this paper. In the first stage, the quantum bacterial foraging (QBF) algorithm is used to select emergency transit points and divide the medical assistance points. In view of the imbalance of remaining capacity in QBF division, an improved division method (quantum bacterial foraging with capacity constraints (QBFwCC)) is proposed and a ‘helicopter–vehicle’ medical material combined transportation network structure is constructed in consideration of capacity constraints. In the second stage, a transportation route optimization model based on clustering is established to determine the specific transportation route from the emergency transit point to the medical assistance point. The performance of the method proposed in the paper was analyzed through experimental COVID-19 simulation and compared between QBF and QBFwCC. The results show that the method not only achieves the goal of optimization, but also effectively reduces the number of vehicles.

Optimization of Urban Cold Chain Transport Routes under Time-Varying Network Conditions

Given the time-efficient characteristics of urban cold chain transportation and the time-varying characteristics of urban road speed, customers encounter the problem of limited vehicle path optimization due to a fuzzy time window. An optimization model of urban cold chain transportation with the objective function as the minimum total cost is constructed under the premise of service reliability, and an artificial immune particle swarm optimization algorithm is designed to solve the model. For an empirical analysis of Xiamen’s cold chain transportation, a two-stage solution involving “static optimization and dynamic optimization” is used to verify the effectiveness of the model and the practical value of this research. Results show that the time-varying model can effectively reflect the situation of urban road transportation and satisfy the timeliness requirement of urban cold chain transportation.

Optimization model design of cross-border e-commerce transportation path under the background of prevention and control of COVID-19 pneumonia.

In order to better accelerate the transition from traditional trade to cross-border e-commerce, a cross-border e-commerce transportation route optimization model was designed in the context of the prevention and control of new crown pneumonia. Against the background of the new coronavirus pneumonia, through the analysis and research of the current situation of domestic and foreign e-commerce logistics, optimize the cross-border e-commerce logistics distribution model, establish an environmental model, and use efficient search algorithms to search for walking paths that meet environmental requirements. Based on the Dijkstra algorithm model of demand, and based on the linear relationship between demand and delivery distance, an optimal route selection model is established to select the optimal route with the shortest total travel distance. The simulation results show that the cross-border e-commerce transportation time of this model is within 13 h, which is shorter than that of the traditional model. The search efficiency of the optimal route for cross-border e-commerce transportation is higher, and the time for cross-border e-commerce transportation is shorter.

An Optimization Route Selection Method of Urban Oversize Cargo Transportation

In order to select the optimal transportation route among alternative transportation routes more accurately and objectively, the choice of urban oversize cargo transportation routes was studied by taking the optimization weight–TOPSIS combination method for specific calculations. This model, based on an entropy weight method, cloud model, and TOPSIS method, combines the superiority of the cloud model for reflecting the randomness and discreteness of subjective evaluation with the advantages of the TOPSIS method in dealing with the problem of multi-objective programming. Through selecting and classifying several the main road influencing factors of urban oversize cargo transportation, based on the data of four urban roads, the entropy weight method is used to initially determine the weights of each influencing factor, the cloud model is used to optimize weights, the TOPSIS method is used to compare and evaluate the paths, and the optimal transportation route is selected on this basis. The results showed that the optimization weight–TOPSIS method is scientific and accurate for the multi-objective planning of oversize cargo transportation route selection, and solves the problem of the impact of subjective factors in existing methods and the difficulty of processing multiple influencing factors. The Pearson consistency test results show that the Pearson correlation coefficient between the proposed method and the actual oversize cargo transportation route selection is 0.995, which is higher than the calculation results without using the combination weight.