Optimal Transportation Routes Research Articles

Use of criteria for process optimization elevator complex routing

The goal of the work. The purpose of this work is to describe the optimality criteria for determining the direction of solving the problem of optimizing transport and technological routes of grain products at the elevator complex. Research methods. An analytical research method was applied to determine the technological characteristics of the elevator complex line and the dependence of the quality of transported products on the constructed transportation route. A mathematical method is applied to describe the constituent elements of the optimization criteria. Obtained results. One of the directions for increasing and improving the technological process at the elevator was determined, by improving the control algorithms in the direction of optimizing the technological processes of the elevator according to many criteria. According to optimization criteria, to ensure optimal transportation conditions, minimum losses, minimum transportation time, minimum energy consumption, and minimum length of the laid transportation path should be used, therefore, a description of the main criteria that can primarily affect the efficiency of the elevator complex was performed. Scientific news. The direction of solving the problem of optimization of transport and technological routes is determined. Analytical derivation of the minimum energy consumption criterion and the minimum grain fight criterion. Practical value. Optimization of the elevator complex to ensure variable transportation of grain masses, which will affect the productivity and quality of the technological process of the elevator complex.

A System of IoT Devices to Prevent the Underloading And Overloading of Railway Wagons

Coal transportation poses substantial obstacles for corporations such as Coal India Limited (CIL), including concerns with route selection, rehandling, precise weighing, demurrage costs, and underloading fines. CIL's failure to adopt optimal transportation routes has resulted in needless costs. Coal rehandling at depots has proven expensive, and there are disparities in coal transportation rates. The lack of weighbridges makes accurate weighing difficult, resulting in probable pilferage. Demurrage costs have been a financial hardship, and railway carriages underloaded have resulted in fines. To address these challenges, the proposed IoT solution seeks to reduce financial losses, improve operational efficiency, increase accountability, ensure regulatory compliance, provide real-time monitoring, automate alerts and penalties, improve communication, improve data security, provide multilingual support, and, ultimately, increase revenue. This idea aims to change coal transportation by increasing efficiency, transparency, and cost-effectiveness for CIL and the government. However, it incurs initial expenses and complications associated with IoT deployment, maintenance, and regulatory compliance. Keywords: CIL, IOT, efficiency, pilferage.

Resource allocation and route planning under the collection price uncertainty for the biomass supply chain

The escalating severity of global warming has drawn worldwide attention to ecological problems. Nevertheless, with the introduction of environmental policies, biomass resources have been effectively developed as a renewable energy source. This paper investigates an advanced biomass supply chain design wherein biomass resources are initially converted into bio-oil through widely distributed fast pyrolysis facilities, and are subsequently transported to a centralised biorefinery for further refining into biofuels. This novel biomass supply chain addressed three key issues: (1) The number of fast pyrolysis facilities, (2) The allocation of resources, and (3) The routes of resources transport. In respect of these problems, a two-stage stochastic mixed integer programming model is established to minimise the total cost of the biomass supply chain considering the uncertainty collection price of fast pyrolysis facilities. A hybrid simulated annealing algorithm which incorporates the sample average approximation method is proposed to solve the stochastic model and is effectiveness for large-scale examples. Finally, a sensitivity analysis is performed using the proposed algorithm and the results show that the proposed stochastic model outperforms the deterministic model under uncertain collection price. The model allows optimising the biomass supply chain economic performances and minimise financial risk on investment by determining the fast pyrolysis facility locations, reasonable resource allocation and optimal transport routes under uncertain collection price.

Exploring logistics transport route optimization: An algorithmic study based on RFID technology

With the rapid growth of e-commerce, logistics companies face challenges in efficient routing and scheduling to meet dynamic delivery demands. This paper proposes a novel logistics scheduling model to optimize vehicle routing using Radio Frequency Identification (RFID) technology. A vehicle scheduling model is developed. The random customer demand and service time are solved using an adaptive taboo search algorithm combined with a nearest neighbor algorithm. Comparative experiments demonstrate the performance of the improved method in completing tasks and reducing queueing time compared to other methods. A case study of route optimization for a logistics company shows the model can recommend optimized routes that reduce total transportation cost by over 25% compared to using RFID alone. The results highlight the potential of the proposed technique to enhance logistics efficiency. Limitations and future work are discussed.

Route Optimization of Hazardous Material (Hazmat) Transportation with Risk Equity and Time-Varying Risk

This paper strives for route optimization of hazardous material (hazmat) for given probabilities and consequences. We aim to not only develop a model to determine the route with the least total risk and cost, but also pursue risk equity from three perspectives of government, enterprises, and society in the route optimization. Specifically, this paper reduces the differences of population exposure risk among road segments by using the threshold setting method and decreases the differences of environmental risk by minimizing the risk compensation cost caused by the additional environmental risk exceeding its average for each road segment. In addition, this paper analyzes the impact of the time-varying characteristics of risk and risk equity and proposes a multi-objective route optimization model which considers the minimization of total risk, cost, and risk differences under time-varying conditions. Finally, the ε-constraint method and an improved genetic algorithm are used to optimize the model, which is applied to a case study involving hazardous materials transportation route optimization in Shanghai, China. The resulting analyses indicate that risk equity can be improved by setting a proper threshold to acquire feasible paths and by minimizing the compensation cost to control the differences of environmental risk. Considering variance of time in the route optimization may lead to a route with lower risk and better risk equity.

Multimodal network path optimization based on a two‐stage algorithm in the perspective of sustainable transport development

AbstractThe environmental issues brought on by carbon emissions from transport have risen to prominence in recent years. More and more academics are using the multi‐objective path optimization method to solve the multimodal optimization problem from the standpoint of sustainable development in order to address the environmental issues brought on by the transport process. The research proposes a two‐stage method to handle multi‐objective optimization convergence and simplify multimodal transport path optimization. In the first stage, a fuzzy C clustering model is established, and based on the clustering results, the multimodal transport network nodes are identified. In the second stage, a multimodal transport multi‐objective path optimization model is established, and the optimal path is solved using a genetic algorithm. The research method was applied in the Bohai Rim region. Results indicated that the fuzzy C‐clustering method and the genetic method were able to select the optimal node city, thus solving the actual site selection problem of multimodal transportation networks. Using the FCM model, the 86 city nodes were categorized into four types, leading to the establishment of the most proficient multimodal transportation network in the Bohai Rim region. Using a genetic algorithm for optimization, a stable state is reached after 25 iterations. In the validation experiment on path optimization, the cost was reduced by 47.12% compared to the minimum single objective time, and transportation carbon emissions saw a reduction of 28.23%. Similarly, compared to the lowest target for transportation carbon emissions, the cost was reduced by 39.48% and the time was reduced by 38.12%. Compared to the lowest target for transportation carbon emissions, the time was reduced by 32.02% and the carbon emissions were reduced by 19.23%. Notably, the transportation multi‐objective path optimization model showed significant improvement compared to the single‐target model. The research method has been proven to be superior, and can offer the most optimal transportation route guidance for participants in multimodal transportation. Furthermore, it can effectively tackle the issue of node selection convergence and multi‐objective optimization, while also serving as a valuable source of data to support the theoretical advancement of multimodal transportation network path optimization.

Route Optimization for Hazardous Chemicals Transportation under Time-Varying Conditions

Since accidents of hazardous chemicals transportation will cause serious loss to the surrounding environment and lives and properties, this paper studies the transportation route optimization problem of hazardous chemicals under dynamic time-varying conditions. Combined with the goal of green sustainable development, a multiobjective nonlinear optimization model is constructed to minimize the transportation risk, transportation cost, and carbon emissions generated in the transportation. The model is solved by the improved Fast Non-Dominated Sorting Genetic Algorithm with Elite Strategy (NSGA-II) algorithm. The effectiveness of the model and the algorithm are tested on the Sioux Falls network. The experimental results show that under time-varying conditions, a vehicle’s departure at different times will generate different transportation costs and risks. Therefore, enterprises need to rationally arrange the departure time of vehicles according to the time windows of customer nodes and road conditions. In additio, from the relationship between the optimization objectives, in order to achieve green, sustainable and low-risk transportation, enterprises should first reduce their transportation costs.

Optimization of logistics intermodal scheduling model based on counting and efficiency in the context of low carbon economy

Abstract It is of great significance to study how to reasonably allocate materials and optimize distribution routes in the context of a low-carbon economy to improve the efficiency of logistics work. This paper constructs a low-carbon economy logistics intermodal dispatch optimization model on the basis of the counting and efficiency model. It carries out the optimization of transport routes under the consideration of logistics transportation externality cost. Its total generalized transportation cost is minimized as the goal of optimization modeling, establishing the cargo transportation operation flow, and outputting the logistics flow distribution and path optimization scheme under the whole integrated transportation network. The multimodal transportation optimization model is solved by using triangular fuzzy theory to select the optimal scheduling scheme, and simulation analysis is carried out using an earthquake-stricken area as an example. The results show that the comprehensive satisfaction degree of the disaster victims of the rescue plan obtained by the proposed intermodal logistics scheduling optimization model is 0.9022. At the same time, the value of GAP obtained by this paper’s method for optimization in a multi-scenario deterministic environment is smaller than that of the traditional method by 0.002~0.068, and the running time of this paper’s method is less than that of the conventional algorithm by 81.9~1400.5 s. The study verifies the validity of the proposed intermodal logistics scheduling model and is useful for improving logistics dispatching and path optimization. The study confirms the effectiveness of the model proposed in this paper, which has some applications and promotion potential for improving logistics deployment and other auxiliary decision-making.

Investigation of Simulated Annealing and Ant Colony Optimization to Solve Delivery Routing Problem in Surabaya, Indonesia

This research emphasizes the importance of efficient goods delivery services because it is essential in maintaining the sustainable supply chain's continuity and applying optimization techniques, specifically the Traveling Salesman Problem (TSP), in determining optimal transportation routes. It compares the effectiveness of the Simulated Annealing (SA) and Ant Colony Optimization (ACO) in finding the shortest routes to minimize operational costs. This study compares the performance of the SA and ACO algorithms. It shows that both provide improved routes compared to the existing routes, with the SA achieving shorter distances, 17.4% smaller than the existing route.

Modelling of optimal transportation route selection based on artificial bee colony algorithm

Modelling of optimal transportation route selection based on artificial bee colony algorithm

MODEL OF TRANSPORT SAFETY ASSESSMENT IN MULTIMODAL TRANSPORTATION SYSTEMS

In this paper methods, criteria and models of safety assessment of multimodal transportation systems are investigated. Today, new types of transportation systems are formed – multimodal transportation systems, which may be defined as the result of the synthesis of several transport systems, where different modes of transport are effectively interact. The need for such systems was formed due to the peculiarities of each mode of transport, its technological and technical characteristics, which restrain the ability to compete and promote transport interaction. In this context, the problem of transport safety assess of multimodal freight transportations becomes highly important. An analysis of modern scientific researches on topic of transport safety is conducted. Unfortunately, the considered approaches to transport safety have a set of disadvantages if the complex systems are considered in form of, for example, combined, multimodal or intermodal transportations: the problem of local optimum; the problem of safety management in case of transport company is not the actual infrastructure owner; the problem of unifying estimates for several modes of transport, and so on. The system’s safety depends on its integrity and sustainable development, which is directly dependent on the objective conditions of its formation, development and operation. At the same time, the state of safety is directly dependent on subjective factors, the purpose of which is to ensure security, i.e., to preserve the integrity and maintain sustainable development and optimal functioning of the system. Thus, there is a conditional field of protection of transport system objects, which provides counteraction to a set of existing or perceived threats. In this context, modelling the transport safety assessment of multimodal freight is relevant and requires appropriate scientific developments. In the research, methods of mathematical modelling of transport systems were used in order to develop methodological approach that could be potentially used in improving the multimodal freight transportation safety. A methodical approach to safety assessment on the example of multimodal transportation, which takes into account the drawbacks of existing studies, is proposed. The practical application of developed model was demonstrated on the existing system of multimodal transportation. The developed safety assessment method may be potentially used both to assess the transportation route safety level and as key factor in optimal transportation route designing.

Research on transportation management model of COVID-19 medical waste: a case study in Beijing, China.

During the COVID-19 pandemic, disposable masks, protective clothing, gloves, and nasopharyngeal swabs collected by nucleic acid testing formed a large amount of medical waste. Medical waste has strict temporary storage time requirements in hospitals, which need to be transported to medical waste disposal plants within the specified time. However, as most of disposal plants are far away from downtown, they also need to be responsible for the transportation and disposal of medical waste in many hospitals, and put forward higher requirement for transportation routes. Rapid and safe disposal of all types of medical waste generated by COVID-19 is crucial to the prevention and control of the epidemic. This paper designs the transportation route optimization model using Anylogic simulation software based on the regional distribution of 118 tertiary hospitals and 2 large medical waste disposal plants in Beijing, China. At the same time, transportation routes of 118 tertiary hospitals in the morning peak, evening peak, all-day, and ordinary periods were simulated based on the Beijing traffic index in 2017. On this basis, through the analysis of the simulation data, the selection of medical waste transport routes for 118 tertiary hospitals in the morning peak, evening peak, all day, and ordinary periods is further clarified, so as to ensure that medical waste can be transported to the medical waste disposal plant in the shortest time. The shortest path and fastest speed transport mode, medical waste transport data set, and the selection of transport mode of 118 tertiary hospitals formed by this research provide certain reference experience for the rapid and safe transport of medical waste during the epidemic period, and also provides corresponding data support for medical waste transportation management in the post-epidemic era and medical waste transportation decision-making when facing major public health problems.

МАРКЕТИНГОВА СТРАТЕГІЯ РОЗВИТКУ ЛОГІСТИЧНИХ ПОСЛУГ В ГЛОБАЛЬНОМУ ЕКОНОМІЧНОМУ ПРОСТОРІ

The article defines the role of marketing strategies for the development of logistics services in the international economic space. The study analyses the challenges faced by logistics companies in connection with globalisation and identifies the key aspects of international marketing that affect the success of logistics services management. The article discusses the need to adapt marketing strategies to different cultures and economic conditions inherent in different countries. The article analyses effective methods of promoting logistics services in international markets and examines important aspects of branding and communication to ensure success in logistics service management. The article examines current trends in the international marketing of logistics services and identifies strategies for adapting to changes in the global economic environment. The authors explore the role of effective logistics service management in creating competitive advantages in international markets, paying attention to supply chain optimisation and improving the quality of customer service. The article also discusses strategies for expanding the network of logistics services in different regions of the world, analyses the issues of choosing optimal transport routes and ensuring delivery reliability. The authors improve approaches to logistics risk management and cost-effectiveness on a global scale. In particular, the article discusses strategies for increasing competitiveness, using flexible pricing and developing customer service strategies to ensure sustainable success in the global logistics segment. The article proposes a structural and logical model for the formation of a marketing strategy for the development of logistics services in the global economic space, focusing on their development in the international economic space. The article studies challenges that companies face in logistics management and identifies key aspects of international marketing aimed at effective positioning of logistics services in the global market. The study provides practical recommendations for improving the efficiency of international marketing of logistics services and managing their development. Particular attention is paid to strategies for expanding the network of logistics services in different regions and developing efficient transportation methods without the use of digital tools. Additionally, the issues of logistics risk management and cost accounting in the global market are considered

Life-cycle assessment of microwave-assisted pyrolysis of pine sawdust as an emerging technology for biodiesel production

Although biofuels are often presented as a renewable and eco-friendly substitute to fossil fuels, it is crucial to have a comprehensive understanding of the complete environmental consequences of biofuel production to make well-informed choices about their usage. This study evaluated the environmental impacts of producing biodiesel from microwave-assisted pyrolysis (MAP) of pine sawdust using life-cycle assessment. A cradle-to-gate system boundary approach encompassing pine cultivation, biomass pre-processing, pyrolysis, and biofuel synthesis via transesterification was used. The ecoinvent v3.7 in openLCA v2.0 software was used to assess the environmental sustainability of the system. The ReCiPe 2016 (H) midpoint impact assessment methodology was used to analyze 18 environmental impact categories. The results showed that producing 1 kg of biofuel from MAP of pine sawdust had environmentally favorable impacts for most categories except global warming potential (1.18 kg CO2 eq.), photochemical oxidant formation (0.71 kg NMVOC eq.), and human toxicity (2.46 kg 1,4-DCB eq.). Biomass production contributed significantly to global warming, freshwater ecotoxicity, human toxicity, and marine ecotoxicity. Pyrolysis contributed 33 % of global warming potential due to non-condensable gas emissions. Biofuel synthesis impacted human toxicity, photochemical oxidant formation, and terrestrial ecotoxicity, mainly due to methanol use. Implementing sustainable practices such as using organic fertilizers, optimization of transportation routes, implementing gas cleaning technologies and effective waste management practices can enhance the environmental performance of this biofuel production system.

Eco Efficiency Optimization of Municipal Solid Waste Management

Abstract: Municipal solid wastes, commonly referred to as trash or garbage, are the solid wastes generated from human activities. A number of these wastes are extremely toxic and infectious. The uncontrolled and unscientific way of dumping such wastes have raised the number of incidents of hazards to human health. One among the important aspects which gains more impact on sustainability of the environment is management of municipal solid waste. A case study of Juhu (MCGM) has been selected for effective and efficient management of municipal solid waste. The main objective of the research is to seek out an optimal route for transporting the rubbish from dumper bins and from temporary transfer stations to the ultimate dumping yard. The research work has been administered in two stages, namely data collection within the first stage and data analysis for optimization within the second stage. For locating the optimal transportation route, VRPTW model is employed in the GIS and GA environments. The proposed study is concentrated on finding the optimal route in transporting the MSW from dumper bins and temporary transfer stations to the dump-yard. MCGM must operate 90 such vehicles in 6 trips. . When time window is employed for vehicle routing, resources like labours and vehicles can be effectively managed and utilized. Due to the time window, it is easier for the highest-level officials to manage both labour and transportation vehicles.

Use of the geospatial technologies and its implications in the maritime transport and logistics

All the shipping industry and also ship building (shipyards) are under a complex process of digital transformation (DT), and so are the maritime ports as part of this logistic chain of significant importance. This paper aims to review the successive information technology (IT)-based generations that impacted the maritime transport and logistics (computer-based optimization of transport routes; use of intelligent sensors and IoT; position monitoring by using geospatial technologies and databases; intelligence-based decisions), to identify their main features, and to propose an autonomous vessel-port management system that can be implemented in the future. The role of the geographic information system (GIS) is emphasized – as GIS-based electronic route optimization that allows ships to follow new paths and deliver goods in the most economical and efficient way; GIS-based location precision with the use of on board and ashore GIS-based sensors (electro-optics, remote sensing, LiDAR). The shipping digitalisation process is heading towards a totally autonomous and at the same time safe and reliable ship. Complete autonomy could be reached by adjoining artificial-intelligence controlled systems designed to navigate and operate the ship and that are equipped with sensing and analysis tools, situational awareness, planning, and control capabilities. The Vessel Traffic System (VTS) of the future needs innovative technologies and methodologies to be developed. The desired systems will automatically collect and process data with high precision, will provide input to decision-making systems, and suggest evasive maneuver; to deal with hazards and systems failure without human intervention onboard. The use of new technologies comes with new types of risks specific to maritime transportation and seaports (spoofing, data manipulation, cyber-attacks etc.) The implications of the findings are important for all stakeholders involved in maritime transport and associated logistics (seaports).

PENERAPAN METODE SAVING MATRIX DALAM PENENTUAN RUTE TERPENDEK PENGANGKUTAN SAMPAH DI KABUPATEN KUBU RAYA

The process of transporting waste from the Waste Disposal Site (TPS) to the Final Disposal Site (TPA) is one of the problems in Kubu Raya district that needs attention. This is because the volume of waste in each TPS in Kubu Raya varies, and the number and capacity of transport vehicles provided by the PUPR Office of Kubu Raya is limited. Of course, these problems affect the distance traveled by the transport vehicle, travel time and costs incurred. Therefore, it is necessary to choose the optimal transportation route. The route is said to be optimal when each TPS is transported one way and does not exceed the capacity of the conveyance, so that the total distance obtained is the minimum total distance. The existing problems are then modeled in mathematical form and solved using the Saving Matrix method. This method combines destination points that can be traversed one way by paying attention to the volume of demand for each destination so as not to exceed the vehicle capacity. Based on the research results obtained four optimal vehicle routes with a total distance of 141.6 km. with details for the distance of vehicle route one which is 41.5 km, vehicle route two is 35.95 km, vehicle route three is 35.9 km, and vehicle route four is 28.25 km. This shows that the application of the Saving Matrix method provides more efficient results compared to the previous route of 162 km

Intelligent Path Planning for AGV-UAV Transportation in 6G Smart Warehouse

Recently, deep reinforcement learning (DRL) has attracted increasing interest in the field of intelligent navigation and path planning in smart warehousing. The latest imitation augmented DRL (IADRL) model has achieved good performance for the cooperative transportation tasks of automatic guided vehicles (AGVs) and unmanned aerial vehicles (UAVs). However, this model cannot always transport target cargoes with the optimized policy due to premature convergence. Therefore, we propose an intelligent path planning model for AGV-UAV transportation in this paper. The proposed model utilizes the proximal policy optimization with covariance matrix adaptation (PPO-CMA) in the imitation learning and DRL networks, which enables the AGV-UAV coalition to plan the optimal transportation route at a lower cost. Experiments conducted in simulation warehousing scenarios demonstrated the proposed model and improved the accumulated training reward by more than 10%, outperforming the existing state-of-the-art models in terms of effectiveness and efficiency.

Investigating the mitigation of greenhouse gas emissions from municipal solid waste management using ant colony algorithm, Monte Carlo simulation and LCA approach in terms of EU Green Deal

This study majorly aimed to determine the effect of optimization on transport routes on the reduction of greenhouse gas (GHG) emissions from municipal solid waste management (MSM) within the scope of European Union (EU) Green Deal. Optimization of collection and transportation routes has been regarded as an effective methodology in order to mitigate the GHG emissions of municipal waste management, recently. Optimization of routes has been obtained using ant colony algorithm (ACA) and Monte Carlo simulation, in this study. In this context, this study investigated to reduce GHG emissions from municipal waste management using optimization of transportation routes in Diyarbakir city in Turkey. Firstly, GHG emissions which are carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions from waste collection and transport have been calculated using a new developed model based on Tier-I method. Then, Monte Carlo simulation has been used to figure out the GHG emissions. Finally, life cycle assessment (LCA) approach has been applied to determine the GHG emissions. According to the route optimization resulting ACA methodology, nearly 47.43% of reduction on each GHG emissions. Approximately, 58%, 38% and 51% of reduction on CO2, CH4 and N2O emissions respectively has been achieved, in the result of the route optimization using Monte Carlo simulation. The results of LCA methodology revealed that the reduction reached up 45.71% on GHG emissions in terms of Global Warming Potential (GWP). The reduction amounts have been overlapped with each other.

Spatiotemporal interaction pattern of the Beijing agricultural product circulation

Identifying the spatiotemporal interaction pattern of agricultural product circulation (APC) is crucial for agricultural resource adjustment and food security. Current studies are mostly based on static statistical data over an entire year or a specific period, which cannot describe the spatial pattern of APC and its seasonal variation on a fine spatiotemporal scale. Thus, this study extracts an APC trip chain based on national truck trajectory data and constructs the flow network of the Beijing APC with the city as the spatial unit and the season as the temporal unit. The spatial interaction pattern and seasonal variation in APC are then analyzed from the network spatial form, city node function role, and transportation corridors. The results are as follows: (1) Compared with methods based on static statistical data, the proposed method provides a more complete and refined depiction of the spatiotemporal interaction pattern of APC. (2) The flow network of the Beijing APC involves 316 cities in China, of which 143 cities play a major role with typical seasonal characteristics. These cities can be divided into perennial core cities, perennial major cities, core cities in winter-spring, major cities in winter-spring, core cities in summer-autumn, and major cities in summer-autumn, contributing 2.6%–40.3% to the Beijing APC. (3) There are 6 transportation corridors for the Beijing APC. The Beijing-Tianjin-Hebei corridor and coastal corridor contribute 53.5% and 12.8% of the annual supply, respectively, with a balanced supply in all seasons. The Beijing-Kunming corridor and Beijing-Guangzhou corridor contribute 14.3% and 9.0%, respectively, with much higher supplies in winter and spring. The northeast and northwest corridors contribute 7.3% and 3.3%, respectively, mainly in the summer and autumn. These results help deepen the understanding of agricultural product supply patterns and provide a reference for the design and optimization of agricultural product transportation routes.