Transportation Costs Research Articles

On concentration of the empirical measure for radial transport costs

Let μ be a probability measure on Rd and μN its empirical measure with sample size N. We prove a concentration inequality for the optimal transport cost between μ and μN for radial cost functions with polynomial local growth, that can have superpolynomial global growth. This result generalizes and improves upon estimates of Fournier and Guillin. The proof combines ideas from empirical process theory with known concentration rates for compactly supported μ. By partitioning Rd into annuli, we infer a global estimate from local estimates on the annuli and conclude that the global estimate can be expressed as a sum of the local estimate and a mean-deviation probability for which efficient bounds are known.

Logistics Model for Indonesia’s National Freight Model System: From a Deterministic to a Stochastic Framework

One of the components of a new model, called INTRAMOD, for Indonesia’s domestic freight transport is the logistics model. The logistics model describes shipment size choice and the choice between five different transport chain alternatives involving four main modes: truck, train, vessel, and plane. This paper presents the work to forecast the disaggregate transport chain and shipment size choices for Indonesia’s domestic shipments by applying a deterministic and a stochastic approach. Using a standard economic order quantity model with a consolidation assumption, a deterministic approach is used to determine the transport chain and shipment size, minimizing total logistics cost. As an alternative for this, a stochastic model aims to improve the logistics choice modeling by employing data on the manufacturer’s revealed preferences and stated preferences about only the transport chain choice. The chosen specification for the stochastic approach is utilizing the multinomial logit model. Using the demand elasticities for all alternatives with respect to changes in its transport cost, a comparison will be made between the two approaches. In addition, it is concluded that the deterministic model is susceptible to sticky and flip-flop behaviors. In contrast, this characteristic is absent from the stochastic approach.

Hydrogen supply chain for future hydrogen-fuelled railway in the UK: Transport sector focused

Though being attractive on railway decarbonisation for regional lines, excessive cost caused by immature hydrogen supply chain is one of the significant hurdles for promoting hydrogen traction to rolling stocks. Therefore, we conduct bespoke research on the UK's hydrogen supply chain for railway, concentrating on hydrogen transportation. Firstly, a map for the planned hydrogen production plants and potential hydrogen lines is developed with the location, capacity, and usage. A spatially explicit model for the hydrogen supply chain is then introduced, which optimises the existing grid-based methodology on accuracy and applicability. Compressed hydrogen at three pressures, and liquid hydrogen are considered as the mediums, incorporating by road and rail transport. Furthermore, three scenarios for hydrogen rail penetration are simulated respectively to discuss the levelised cost and the most suitable national transport network. The results show that the developed model with mix-integer linear programming (MILP) can well design the UK's hydrogen distribution for railway traction. Moreover, the hydrogen transport medium and vehicle should adjust to suit for different era where the penetration of hydrogen traction varies. The levelised cost of hydrogen (LCOH) decreases from 6.13 £/kg to 5.13 £/kg on average from the conservative scenario to the radical scenario. Applying different transport combinations according to the specific situation can satisfy the demand while reducing cost for multi-supplier and multi-targeting hydrogen transport.

Using Design-Based Research to Develop the Learning Outcomes of a Curriculum-Based Environmental Citizen Science Project

The Intertidal Monitoring Project (IMP) is a local, curriculum-based citizen science project intentionally designed to support the development of science competencies in elementary students. The focus of the IMP is the Research Days, where students follow an established scientific protocol to collect monitoring data on an introduced species of clam in British Columbia, Canada. The IMP represents a unique program to study because the school district funds transportation and programming costs so that all grade five students can engage in authentic place-based scientific research. A design-based research (DBR) approach was used to develop and refine the IMP activities between 2014 and 2023. This research is focused on a DBR Evaluation/Reflection phase that qualitatively assessed learning outcomes during the beta testing of a supplementary classroom activity. Student- and teacher-generated data were collected to understand the process of a class “coming to know” science and its community of practice during the IMP activities. This included student learning artefacts and a teacher interview. The findings show that participation in IMP activities: i) fostered the development of science competencies in a grade five learning community; ii) did not promote science identities; and indicated that iii) the Nature of Science (NOS) required more explicit instruction. Student-teacher-scientist partnerships (STSPs) emerged as a critical design element of curriculum-based citizen science.

Boundary-layer structures arising in linear transport theory.

We consider boundary-layer structures that arise in connection with the transport of neutral particles (e.g., photons or neutrons) through a participating medium. Such boundary-layer structures were previously identified by the authors in certain particular cases [Phys. Rev. E 104, L032801 (2021)2470-004510.1103/PhysRevE.104.L032801]. Extending the previous work to anisotropic scattering and general Fresnel boundary conditions, this contribution presents computational algorithms which (1) resolve the aforementioned layers as well as previously unreported boundary layers associated with Fresnel boundary transmission and reflection, and (2) yield accurate simulations at fixed computational cost for transport under phase functions with arbitrarily strong anisotropy. The present paper additionally includes (3) Mathematical proofs which justify the numerical methods proposed for resolution of boundary-layer structures. The impact of the new theory on algorithmic performance is demonstrated through a series of 1D computational benchmarks that emulate typical photon- and neutron-transport applications such as, e.g., optical tomography, and nuclear reactor analysis and design. Experimental results for transmission of photons through turbid media are presented, exhibiting close agreement between simulated and experimental data. As illustrated by means of a variety of numerical results, the proposed boundary-layer-based approach tackles transport problems with unprecedented accuracy and efficiency.

THE IMPACT OF E-COMMERCE ON OPERATIONAL COST EFFICIENCY IN MODERN BUSINESSES

This study explores the impact of e-commerce on operational cost efficiency in modern businesses. E-commerce platforms enhance cost savings through advanced inventory management, streamlined supply chain processes, and reduced overhead. Key findings include improved inventory control with real-time tracking, lower transportation costs via direct-to-consumer models, and significant savings on physical retail space expenses. Additionally, digital marketing strategies offer cost-effective advertising solutions. Challenges include the need for investment in IT infrastructure and cybersecurity. Strategic investments and continuous innovation are crucial for maximizing e-commerce benefits.

Exploring the dynamic impact of the Northern Sea Route on China-Europe multimodal transportation competition in the context of the Belt and Road Initiative

As Arctic sea ice continues to melt, the Northern Sea Route (NSR) is anticipated to become the third major China-Europe transportation corridor, alongside the Suez Canal Route (SCR) and China Railway Express (CRE). This study investigates the integration of the NSR into the Belt and Road multimodal transportation network and analyzes its dynamic competition with traditional corridors across heterogeneous regions and markets in China. To achieve this, we developed a novel hybrid multi-criteria decision-making (MCDM) framework to evaluate the NSR's potential as an alternative China-Europe trade route. This framework introduces a new criteria utility function (CUF) and integrates the Bayesian best-worst method (BBWM) and measurement of alternatives and ranking according to compromise solution (MARCOS) method. This approach evaluates and prioritizes routes based on cost, time, reliability, safety, sustainability, and convenience, thereby detailing the NSR's market advantages and business prospects. The findings suggest that simply increasing the frequency of transportation services is insufficient to attract Chinese customers to the NSR. Instead, the route's competitiveness is primarily determined by transportation costs. In future scenarios, the NSR will offer additional route options for China-Europe containerized intermodal transport, potentially serving as a complementary corridor to the SCR and CRE under certain conditions. Coastal and sub-coastal regions north of Fujian Province are potential markets for the NSR, while inland regions far from seaports are better suited for connections via the CRE. Notably, time-insensitive containerized cargoes, such as industrial accessories, mechanical equipment, and metal crafts, exhibit higher potential demand for the NSR. In contrast, time-sensitive commodities like fashion apparel, electronics, and medical devices are more likely to be transported by cross-border railroads due to their urgency. Stakeholders, including government agencies, shipping companies, and exporters, can utilize these insights to optimize China-Europe transport organization and effectively commercialize the NSR.

A Mathematical Model for Green Leaves Diet Using Ranking of Tridecagonal Fuzzy Numbers

This study presents a new way of ranking transportation options using tridecagonal fuzzy numbers. This approach takes into account factors such as demand, supply, and transportation costs, and aims to provide a more optimized solution for these fuzzy environments. With the rising importance of healthy eating habits, particularly emphasizing green leafy vegetables, devising an effective dietary plan becomes imperative. Traditional approaches often overlook the inherent uncertainty and fuzziness in dietary preferences and nutritional requirements. In this context, tridecagonal fuzzy numbers offer a robust framework to represent and analyze uncertain dietary preferences. Our ultimate goal is to promote a green leaf diet that is both affordable and widely available, while also improving the overall health and well-being of the general public. This research contributes to the advancement of mathematical modelling in nutrition science, offering a valuable tool for promoting healthier dietary choices and lifestyle habits.

Multi-objective Optimization-Based Algorithm for Selecting the Optimal Path of Rural Multi-temperature Zone Cold Chain Dynamic Logistics Intermodal Transportation

The road network in rural areas is complex and the infrastructure is relatively backward. The multi-temperature zone cold chain logistics involves agricultural products with different temperature requirements, which requires considering the transportation cost, carbon emission cost, refrigeration cost, and time cost of different temperature zones during path planning, thereby increasing the difficulty of path planning. Therefore, a multi-objective optimization-based algorithm for selecting the optimal path of rural multi-temperature zone cold chain dynamic logistics intermodal transportation is proposed. Based on the analysis of the multi-temperature cold chain collection and distribution model based on multimodal transportation, a multi-objective optimization model is constructed. This model aims to minimize transportation costs, carbon emission costs, refrigeration costs, time costs, and maximize logistics quality, while satisfying constraints such as transfer schedule times, the number of transport mode conversions, transport mode selection, and time continuity. To solve this model, an improved NSGA-II algorithm is adopted, which combines an improved mutation operator, congestion distance calculation, and the C-W saving algorithm to achieve the optimal transport path solution. Additionally, ArcGIS software is used to implement the shortest path planning based on real road networks. The experimental results show that by selecting the road-rail combined transport mode and adopting the D1–D6–D10 transport path, it is possible to transport fresh agricultural products from location A to the distribution center at location B, with the lowest Pareto fitness value. Furthermore, the algorithm's effectiveness is further verified by completing the end-of-life fresh agricultural product distribution task with four multi-temperature refrigerated vehicles. The study also finds that extending or shortening the latest service time window for customers, although it leads to a decrease or increase in the optimal value of the algorithm's objective function, has little impact on the average distribution time and transport vehicles. These findings provide new theoretical and practical guidance for the path selection of multimodal transportation in multi-temperature cold chain logistics, with significant theoretical and application value.

Research on Optimizing Human Resource Expenditure in the Allocation of Materials in Universities

This paper establishes a multivariate function model for natural human load-carrying walking in some typical scenarios such as college equipment and material relocation by students and a large amount of identical freight relocation in commercial activities. For classified material relocation needs and constraints, we obtain the relationship between walking speed and load weight for a single person, as well as the time cost for different round trips. By establishing an integer programming model with the minimum total transportation time cost and shelf life as the objective function and the requirements of negative weight and speed as the constraint conditions, we reach the optimal item allocation methods considering time cost and shelf life. We discover that there is an approximate linear relationship between the change in natural walking speed and travel time when the load is small, thus obtaining the time cost of student transportation under different round-trip situations. The Monte Carlo simulation algorithm, which is more efficient compared with other methods such as the integer programming method, is used to obtain the optimal allocation scheme that meets the efficiency and quality requirements. The analysis methods and results can be used as guidance for task scheduling optimization for material relocation in educational organizations as well as commercial agencies.

How to choose mobile energy storage or fixed energy storage in high proportion renewable energy scenarios: Evidence in China

With the large-scale integration of renewable energy and changes in load characteristics, the power system is facing challenges of volatility and instability. Therefore, enhancing the safe and stable operation capability of the power system is an urgent problem that needs to be solved. Mobile energy storage can improve system flexibility, stability, and regional connectivity, and has the potential to serve as a supplement or even substitute for fixed energy storage in the future. However, there are few studies that comprehensively evaluate the operational performance and economy of fixed and mobile energy storage systems. To comprehensively evaluate the economic benefits of large-scale mobile energy storage systems, this paper constructs an overall horizontal cost model for energy storage systems that considers the power system and train transportation system. This model not only introduces the traditional concept of lifecycle cost of energy storage systems, but also considers the costs of traditional transmission lines and battery transportation. Secondly, to achieve simulation of large-scale mobile energy storage system planning and operation, this paper establishes a multi-region power planning and operation simulation (MPO) model and a battery transportation and logistics (BTL) model to accurately reflect the operation mode of fixed energy storage and mobile energy storage in the power system. Finally, taking the actual power grids and railway networks in Northeast and North China as case studies, this article provides an in-depth analysis of the technical, economic, and environmental performance of large fixed and mobile energy storage systems, and conducts a detailed comparison. The research results indicate that under high grid connection ratios (using 75% and 66% as examples), the overall cost of mobile energy storage systems continues to decrease to 1.42 CNY/kWh and 0.98 CNY/kWh. Compared to fixed energy storage at 5.45 CNY/kWh and 4.79 CNY/kWh, it has an absolute economic advantage and shows significant carbon reduction capabilities, reaching 241,800 to 1,394,600 tons. This discovery fully confirms the enormous potential and application value of mobile energy storage in high proportion renewable energy scenarios, providing strong technical support and economic analysis basis for the sustainable development of the power system.

Effects of Paclobutrazol on Reproductive and Vegetative Traits of Phalaenopsis Join Grace 'TH288-4'.

Phalaenopsis is the most popular potted plant worldwide. However, its typically long stalks often lead to increased shipping costs and risks. This study investigates the effectiveness of varying the concentration, timing, and frequency of paclobutrazol (PP333) applications on shortening the stalk of Phalaenopsis Join Grace 'TH288-4'. Concurrently, it also examines the potential for producing visually appealing and single-flower potted phalaenopsis products by means of truncation. Mature phalaenopsis plants were moved to a cool room in the seventh week to induce flowering. Four experimental groups were established based on different PP333 application schedules: the control (CK) group, with reverse osmosis water application in the second week; the T2 group, with a single application in the second week; the T2T3 group, with applications in both the second and third weeks; and the T7T8 group, with applications in the seventh and eighth weeks. The PP333 concentrations used were 250, 500, 750, and 1000 mg·L-1, applied as foliar sprays. The results showed that the shortest stalks, measured from the base to the first flower, were observed in the T2 group treated with PP333 at 750 mg·L-1 and in the T2T3 group with PP333 at 500, 750, and 1000 mg·L-1. These treatments resulted in stalk lengths of 19.18-22.17 cm, which are 67.2-71.6% shorter than the controls. PP333 application had minimal effect on the stalk diameter, pedicel length, flower width, length, and length/width ratio. However, root diameter was thicker in plants treated with PP333 compared with the control plants. For producing single-flower phalaenopsis, a foliar spray of 750 mg·L-1 PP333 is recommended approximately a month before moving the plants to cooler conditions, followed by truncation, retaining only the first flower. As a result, this study establishes a PP333 treatment protocol for phalaenopsis, offering a strategy to effectively shorten the stalks.

A novel development of hybrid maximum power point tracking controller for solar pv systems with wide voltage gain DC-DC converter

Now, the present power generation and distribution companies are working on renewable energy systems because their features are low-level atmospheric pollution, producing less greenhouse pollutants, more reliability, good static performance, and high robustness. In this work, the sunlight Photovoltaic (PV) system is selected because of its advantages are easily available in the atmosphere, high flexibility, zero carbon footprint, easy to maintain, and less transportation cost. However, solar networks produce nonlinear I-V characteristics. Due to the non-linear nature of the solar system, the extraction of peak voltage from the PV module is a very tough task. So, in this article, a variable modified step grey wolf method is integrated with the adaptive-neuro-fuzzy-inference-system to improve the energy production of solar systems. The features of this proposed maximum power point tracking controller are fast identification of the solar system operating point, generating the less fluctuated oriented converter load power, providing more MPP tracking accuracy, less dependence on the solar system installation, and useful for all environmental bad weather conditions. Another problem of solar systems is less voltage production which is improved by introducing a wide voltage gain-boost converter circuit. The features of this converter circuit are less development cost because it does not require more power electronics switches. Here, the proposed IGWM with an AFLC-fed sunlight system is investigated by using MATLAB/Simulink.

Land valuation in the metaverse: location matters

Abstract In urban economics, transportation costs are a key determinant of land value. However, in virtual worlds, these costs are generally limited by the users’ ability to teleport. Drawing from urban and attention economic literature, we propose a theoretical model microfounded on user behavior. The model suggests that the relative value of land parcels hinges on their potential to attract visitors. Our empirical analysis supports this by demonstrating that location remains crucial in virtual worlds and highlighting the role of the teleportation threshold. We discuss the model’s general applicability, reaffirming the significance of location within most virtual worlds.

Powering hydrogen refueling stations with local renewable curtailment – A Lanzhou case study

To promote a hydrogen economy in the near term, in this work, curtailed power from renewable generation in Northwest China is used as the energy source for electrolytic H2. The feasibility of involving methanol as a liquid energy carrier is also explored considering the relatively high cost and safety risk of H2 storage and transportation. Four technology routes including both centralized and distributed versions of pure hydrogen and methanol-mediated supply chains for local H2 consumption at refueling stations are investigated with real-world scenarios in Lanzhou, China. The capacity of existing solar photovoltaics (PVs) is obtained from remote sensing images and a generic supply chain optimization model is developed to compute the minimum levelized cost of hydrogen (LCOH) for each route. Greenhouse gas (GHG) emissions and safety considerations are also assessed for each route. It was found that the green methanol route is the safest with GHG emissions being higher than expected.

Closed-loop supply chain network of end-of-life wind turbines mathematical model proposal considering environmental, employment, and cost reduction aspects

The worldwide climate issue makes wind energy an attractive renewable energy source. Wind energy reduces carbon emissions, energy prices, creates jobs, improves power access, and ensures energy security. The mass of employed materials in wind turbines indicates a lot of potential raw materials when the whole mass is evaluated. Additionally, a new wind turbine costs $2–$4 million. Remanufacturing or using recycled raw materials from end-of-life wind turbines is practical due to the decreased cost of new wind turbines. To ensure sustainability, CO2 emissions and social advantages like employment must be considered. Given the typical life expectancy of wind turbines at 20–25 years, this issue must be addressed globally in the mid-term. The objective of the conducted study is to provide a multi-objective mathematical framework that encompasses the environmental, social, and economic aspects of wind turbines at the end of their operational lifespan. Hence, this study presents a methodical framework for achieving sustainability in the wind energy sector through the implementation of a closed-loop supply chain. Furthermore, a lexicographic solution approach is offered for each objective of the mathematical model, with the aim of providing decision makers with a comprehensive overview of solutions. The methodology employed in this work involves the utilization of a mixed-integer linear programming (MILP) approach to address the closed-loop supply chain for end-of-life wind turbines. Additionally, a lexicographic solution approach is provided to effectively solve the problem at hand. The novelty of this article lies in its examination of the closed loop supply chain network for end-of-life wind turbines, encompassing the social, environmental, and economic dimensions. This study represents the first of its kind to explore these aspects comprehensively. The proposed mathematical model has three objectives which cover the remanufacturing and recycling and aims to minimize CO2 emissions, unemployment, and transportation cost. In order to evaluate the proposed model, Türkiye is utilized as case with real-life data and Gurobi 9.1.2 is utilized. The locations of wind turbines could not be collected individually, and Euclidian distance was used instead of road distance due to a lack of data. These are the main limitations of the proposed study. The study revealed that the TEC and TCE lexicographic approach has the best recycling and remanufacturing cost-to-manufacturing cost ratio, 52.54 %. The least desired result is 74.50 % from CTE.

Economic impact of COVID-19 on patients with type 2 diabetes in Kenya and Tanzania: a costing analysis

IntroductionCOVID-19 affected healthcare access, utilisation and affordability, especially for patients suffering from chronic diseases, including type 2 diabetes (T2D). This study measured the occurrence and magnitude of changes in healthcare...

Morphological characteristics of activated sludge recovered from biological reactors impact on the energy requirement for centrifugal dewatering

The effect of sludge dewatering on handling and transport costs as well as the impact of various parameters like sludge characteristics, the used dewatering equipment and the adopted specific operating conditions, on the efficiency of this step, were considered in the present study. The influence of a laboratory-scale centrifugation for dewatering activated sludge (AS) was also investigated. Additionally, models to describe the relationships between independent variables like centrifugation speed, AS volume and fixed time and dependent variables like the percentage of solid cake (% GS). The used approach was based on the response surface methodology (RSM) along with a central composite design experiment, considering three distinct types of AS: healthy (BS), partially bulking (BF), and deflocculated (BD) sludges. The morphological characteristics of the sludge do have an effect on the operating conditions for the centrifugation, hence the energy consumption for a desired dewatering level. For the case of BS sludge, a centrifugation at 2600 rpm for 10 min, using a 10.3 mL plug, led to a solid cake of 12.65 %, whereas for BD sludge, with a higher centrifugation at 3000 rpm for 17.30 min and a smaller plug volume (8 mL) led to 6.82 %, roughly half of the previous percentage.

Analysis of Regulation of Costs for Operating Buses in a Transport Company

The problem of increasing passenger traffic remains acute for municipal public transport. The value of this indicator is determined by the interest of citizens in this way of making their trips and determines the feasibility of the carrier’s operation. The authors conducted a study of the problems of public transport services in large- and medium-sized cities, which found that the population’s interest in public urban passenger transport has generally been significantly lost. More than 40% of the city population refuses to travel on public transport, half of the population has questions about the reliability of tariff formation, and the same number of people are not satisfied with the regular route network and schedule. City residents increasingly prefer personal vehicles or taxis for their trips, which negatively affects the revenue side of carriers, as well as the level of social comfort and the quality of life of citizens. Efforts to reduce the operating costs of the carrier are aimed at correcting the current situation with urban transport so that tariffs for transportation are more acceptable for passengers. The formation of tariffs for passenger transportation for transport companies is an urgent and complex task. It is necessary to formulate the tariff in such a way as to cover your own transportation costs in the near future and, at the same time, not exceed the psychological threshold for passengers so as not to cause their negative reaction. In addition, since the transportation of passengers by urban public transport is regulated by the authorities, it is also necessary to provide an economic justification for transportation tariffs. This is difficult in the absence of substantiated indicators of consumption rates of material resources in the transport process. To solve this problem, it is necessary to carefully analyze the current costs of operating the bus fleet, as well as forecast costs for future periods. At different periods, researchers have proposed various approaches for planning the cost of operating a bus fleet. The approach we propose is to use standardization of the consumption of material resources, considering the individual operating conditions of the bus fleet and the influence of various factors.

Joint optimization of truck-drone routing for last-mile deliveries in urban areas

This paper presents a joint routing optimization model to satisfy the on-demand customer requirements by minimising the transportation and time penalty costs of trucks and drones, considering the constraints on paths and delivery time of trucks and drones, the drone battery capacity limit, and the customer demands. The improved genetic algorithm is proposed to solve the optimization model followed by the computational experiments demonstrating the superiority of the improved genetic algorithm over the original genetic algorithm in computational efficiency, economy, and punctuality. Further, the comparative analysis demonstrates that the multi-drone joint delivery mode considering the customer demands performs better than the other delivery modes and that the delivery routes can be re-optimised promptly to satisfy the real-time customer demands. The sensitivity analysis on the drone design parameters provides theoretical insights into deploying the size and speed of drone platoons when promoting truck-drone joint delivery in applications.