Freight Agents Research Articles

Semi-dynamic spatial–temporal graph neural network for traffic state prediction in waterways

In the field of maritime traffic, the assessment of waterway passage conditions constitutes a significant research topic, particularly in the context of traffic flow analysis and prediction for busy waterway segments. This is crucial for the regulation of waterways and the enhancement of navigational potential. This paper presents a new semi-dynamic spatio-temporal graph neural network (SDSTGNN) for processing traffic state prediction of waterways. A semi-dynamic spatial graph network (SDSG) module is firstly provided for capture the spatial features, in which a semi-dynamic adjacency matrix based on a predefined adjacency matrix and adaptive matrix is designed for constructing the graph network. Furthermore, to enhances the ability to capture temporal features from input features, a new structure of temporal feature extraction module combining LSTM and Transformer is designed. The comparison of experiments on three datasets illustrate the proposed model SDSTGNN has superior forecasting ability to the compared models. In a comprehensive analysis, MAE, RMSE, MAPE, and WAPE exhibit remarkable reduction averagely on 1–6 period with 6.9%, 5.5%, 18.1%, 9.5%, respectively. By implementation of proposed model, it could optimize ship operations and regulate ship traffic, which benefit in the stakeholders, such as maritime regulatory authorities, ship operators, freight agents, and port management departments.

Learnings from the simulation of use cases in city logistics in the HARMONY project

City logistics simulation can help to provide empirical proof of potential benefits of new solutions in city logistics but decision support tools for such analyses are scarce because of a lack of empirical data and resources. The Tactical Freight Simulator (TFS) is a multi-agent simulator that represents the decision-making of freight agents and individual freight shipments. In this study it is applied to four distinct use cases in city logistics: micro hubs, introduction of zero-emission zones, crowd-shipping and the land use planning of logistic facilities.The simulations show impacts of each development and provide learnings: the type of open or single carrier operation of micro hubs have big local impacts. The impact of freight traffic avoiding zero emission zones can have substantial local impacts. Depending on the configuration of the service, crowd-shipping can lead to more vehicle kilometres. A common finding is the impact of the chosen scenario parameters on the outputs: regulation is important to shape city logistics operations. This also illustrates that, although the technology seems to be ready for innovative solutions, the logistical organisation or business models and policies are not yet well developed.

Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making

Freight transportation plays an increasingly important role in sustainable development. However, freight travel demand has not been understood comprehensively, due to its unique features: freight activities are the result of collaboration among freight agents. It distinguishes freight transportation from passenger transportation, in which travel decisions are made mostly by individuals. Specifically, two processes in the collaboration can be observed: partner selection and joint decision making. Using the supplier-customer collaboration as an example, partner selection is a process for suppliers and customers to evaluate their potential partners and select the best one. Joint decision making allows suppliers and customers to seek common interests and make compromises. As a traditional travel demand model cannot model the two processes effectively, this research develops an innovative econometric model, spatial matching model, to bridge the gap. The proposed model is specified based on freight agents’ behavioral, estimated by Bayesian MCMC methods, and demonstrated by numerical examples. The proposed model and estimation methods can recover the coefficient values in the econometric models, and establish the relationship between the influential factors and the observed matching behavior. The analysis improves the understanding of freight travel demand in a behavioral-consistent manner and enriches the body of freight demand modeling literature.

Significance of Bonded Logistics Parks in China, Enabling Indian Retail Industry for Effective Logistics

Multiple handling and resting of materials at different points in the flow of Supply Chain has come into the limelight in the recent time due to severe cost pressure for the reduction and savings of Logistics costs. The ease of material movement is been on a large focus in-order to achieve cost savings and to have a win-win situation for both the Suppliers and the Customers. With the effect of globalization, the foreign Suppliers are exporting goods to the consignee country by paying customs duty and in-turn the consignee on the receiving end pays import customs duty for the consumption of the goods and on top of it pays an additional storage and handling charges for the Warehousing and Distribution activity in the consignee country. This makes the logistics costs to go up. To tackle this challenge and complexity in the Logistics system, major economies are introducing FTZ - Free Trade Zones or Logistics Parks in major cities. These Free Trade Zones are backed up the concern country’s government and customs authorities. With lot of initiatives coming from the government side but still there is a huge demand gap for these Free Trade Zones or Logistics Parks and many of them are underutilized or rather unoccupied. Still many of the Consumers are relying upon traditional CFA – Custom Freight Agents or other warehouses for getting this service done. But they are missing a big picture of Logistics Cost Savings, Transit time reduction in transferring the goods and the major advantage in tax rebates. At this backdrop, this paper address the major advantage of using the Bonded Logistics Park, developed and promoted by the People’s Republic of China by analyzing the data of an Indian customer who is sourcing more than 70% from China.

Significance of Bonded Logistics Parks in China, Enabling Indian Retail Industry for Effective Logistics

Multiple handling and resting of materials at different points in the flow of Supply Chain has come into the limelight in the recent time due to severe cost pressure for the reduction and savings of Logistics costs. The ease of material movement is been on a large focus in-order to achieve cost savings and to have a win-win situation for both the Suppliers and the Customers. With the effect of globalization, the foreign Suppliers are exporting goods to the consignee country by paying customs duty and in-turn the consignee on the receiving end pays import customs duty for the consumption of the goods and on top of it pays an additional storage and handling charges for the Warehousing and Distribution activity in the consignee country. This makes the logistics costs to go up. To tackle this challenge and complexity in the Logistics system, major economies are introducing FTZ - Free Trade Zones or Logistics Parks in major cities. These Free Trade Zones are backed up the concern country’s government and customs authorities. With lot of initiatives coming from the government side but still there is a huge demand gap for these Free Trade Zones or Logistics Parks and many of them are underutilized or rather unoccupied. Still many of the Consumers are relying upon traditional CFA – Custom Freight Agents or other warehouses for getting this service done. But they are missing a big picture of Logistics Cost Savings, Transit time reduction in transferring the goods and the major advantage in tax rebates. At this backdrop, this paper address the major advantage of using the Bonded Logistics Park, developed and promoted by the People’s Republic of China by analyzing the data of an Indian customer who is sourcing more than 70% from China.

An intelligent decision support system prototype for hinterland port logistics

Port logistics is characterised by a high degree of fragmentation, uncertainty and complexity. In a context with these characteristics, decision support can be of significant value. This study presents the prototype of an intelligent decision support system (DSS) that leads to horizontal and vertical cooperation among freight agents involved in port logistics. A multi-agent simulation model is presented where heterogeneous actions are enabled as a result of an adaptive reinforcement learning algorithm that is inspired by human decision-making strategies. The model combines optimisation modelling and decision theory to operate in a dynamic environment characterised by information asymmetry among agents and dynamic changes over time. A simulation demonstrates the dynamics and convergence to equilibrium of the interactions of heterogeneous agents for delivery and pick up of import/export shipments.In particular, we answer two specific research questions. What is the likely impact of an intelligent DSS in hinterland container transport as a value-added service of port community system (PCS)? How can an optimum cooperative strategy be formulated to meet the dynamic demand and supply of freight agents in hinterland container transport and achieve agility in the age of hyper-competition?By addressing these two research questions we make a specific contribution by developing an agent-based simulation model in a real-world and large-scale case study, by using a reinforcement learning model based on probability matching theory that allows simulating realistically the adaptive behaviour of agents. The results of the simulation of two weeks of container movements indicate huge savings in total transport costs and distance travelled as well as higher utilisation of trucks from the sharing of resources. Moreover, we show that it is strictly better for smaller freight agents to cooperate – a conclusion generated endogenously inside the model as a trade-off between exploration and exploitation. As a result of this prototype simulation, major freight agents will not necessarily benefit from the DSS mainly because they are already using the economies of scale.

Modelling receiver logistics behaviour

There is a need for collaborative urban freight planning and appropriate decision and planning support tools are lacking, resulting in inadequate understanding of how urban freight agents should collaborate and what benefits can be gained from their coalitions. This paper is therefore concerned with including receiver freight agents as autonomous agents into MATSim as a first step towards providing an appropriate decision support system to enable decision makers to determine how a balance between receiver restrictions and urban freight delivery cost can be achieved. The simulation with integrated receiver behaviour is applied to a small case as proof of concept. Results indicate that the newly included receiver agents changed their reordering behaviour autonomously whilst trying to reduce their own cost, confirming that the extended MATSim platform with integrated autonomous carrier and receiver agents demonstrates behavioural sensitivity in the tested scenarios.

Investigation of carriers’ ability to transfer toll increases: an empirical analysis of freight agents’ relative market power

Design of effective freight policies requires a comprehensive understanding of freight agents’ interactions. A critical component of the interaction is the freight agents’ relative market power in determining delivery price, time, and frequency. However, empirical studies of freight agents’ market power are limited. This study explores freight carriers’ market power relative to receivers’ by investigating carriers’ ability to transfer toll increases. A stated preference survey is conducted to understand carriers’ willingness to transfer hypothetical toll increases to receivers. The relationship of various factors and the ability to transfer toll increases is first examined by descriptive statistics. Then, regression models are estimated as a function of respondents’ socioeconomic factors, market conditions, hypothetical toll increases, and other factors. Marginal effects of influential factors are obtained to reveal policy implications.

Freight Flow Modeling in the United States

This paper overviews the different approaches being used by regional planning agencies to estimate the spatial patterns of freight flows within the United States. The narrative moves from a discussion of current modeling practice to consider how on-going research efforts are moving this practice towards new, improved and increasingly involved modeling frameworks. The discussion emphasizes how data limitations have impacted past and current modeling, and how new data sources can help future efforts. Recent advances in both top-down econometric modeling and bottom-up behavioral modeling are described, both capable of contributing to increasingly complex modeling frameworks in support of broad regional and high volume freight corridor applications. How effective future modeling practice will become will depend on its ability to respond to three areas of concern: the need for improved data quality and access; an improved behavioral understanding of freight agents’ transportation choices; and changes in the nature of freight handling technologies and services as well as in the physical nature of the freight itself.

A systematic evaluation of freight carrier response to receiver reordering behaviour

Abstract The fields of behavioural transport modelling has been gaining momentum and many researchers have focused on incorporating some elements of stakeholder behaviour and decision making into their freight planning tools. However, investigation of the literature reveals that few papers are devoted to understanding and integrating logistics behaviour of freight receivers into urban transport simulations, and the impact of receiver reordering constraints on other freight agents in the urban transportation network has not been thoroughly investigated. This paper is therefore concerned with evaluating the impacts that constraints set by freight receivers during reordering have on carriers’ behaviour and cost in an urban freight transport simulation. To achieve this, three key receiver reordering constraints scenarios are simulated: delivery time window durations; delivery frequencies and its associated quantities; and delivery unloading or service time at receiver facilities. These scenarios are then implemented in an agent-based transport simulation and the carrier’s behaviour and delivery cost are evaluated. Results indicate that narrowing time windows could result in delivery and penalty cost increases of up to 93%. Extending unloading times can see costs and penalties increase by up to 111%. Delivery frequency (and therefore order quantity) also has a major impact of the carrier’s cost, with cost increases of up to 142% when requesting more frequent deliveries of smaller quantities. These results confirm that carrier decisions are influenced significantly by changes in receiver reordering behaviour and unnecessary constraints imposed by receivers during reordering could have significant negative implications on the delivery cost of the carrier. This emphasises the importance of finding a balance between restrictions set by supply chain customers during reordering and the cost associated with those restrictions and highlights the importance of finding ways to urge freight agents, especially receivers, to change their current behaviour to lower the total delivery cost of the supply chain.

A multi-scale agent-based modelling framework for urban freight distribution

Abstract Comprehensive modelling of urban freight operations remains a challenge in transportation research. This is partly due to the diversity of commodities transported, shipment units, vehicle types used, stakeholders’ objectives (e.g. suppliers, carriers, receivers), and to the limited availability of data. Thus, existing modelling efforts require several assumptions yet have limited behavioral foundations and minimal interaction between agents. This paper proposes a new agent-based modelling framework, which considers the heterogeneity of urban freight agents and their interactions. Agents include establishments (suppliers, carriers, and receivers) and freight vehicle drivers. Agents’ decisions are structured in three temporal resolutions: strategic, tactical, and operational. A single set of agents is represented throughout all modelling levels ensuring a consistent and sequential flow of information. At the strategic level, establishments’ characteristics and strategic decisions are modelled. These include location choices, fleet constitution, annual production/consumption of commodities, and establishment-to-establishment commodity flows. At the tactical level, shipments are assigned to carriers, who in turn plan their operations in terms of vehicle-driver-route assignments. Finally, at the operational level, the interactions between daily operational demands and transportation network supply are simulated. The supply representation has two different resolution levels (micro or meso) allowing for either detailed or computational efficient simulation. The simulation platform is distinct from previous works, as it explicitly considers planning horizons, replicates agent decision makings/interactions and involves a structure that allows for the propagation of influences bottom-up (e.g., prior simulation travel times on future route choice). The paper describes the simulation platform, constituent models, and illustrates its capabilities using an application of the modelling framework to the city of Singapore.

Agent interactions and the response of supply chains to pricing and incentives

The paper analyzes how the interactions among the freight agents influence the supply chain’s response to public policy initiatives based on pricing and incentives. The fundamental tenet of this paper is that, because of the role played by agent interactions in supply chains, carrier centered approaches are likely to be less effective than comprehensive approaches that exploit the power relations between supply chain agents to achieve policy goals. The paper characterizes the typical roles and interactions between the agents involved in supply chains; provides an economic interpretation of these interactions; and conducts a comparative analysis of the (limited) real-life evidence pertaining to the behavioral impacts of pricing and incentives.

Taste heterogeneity and latent preferences in the choice behaviour of freight transport operators

In this paper we show that individual attitudes of road carriers and their latent preferences toward specific freight service attributes do play a role in determining their mode choices. Specifically, we contribute to the empirical literature on freight agents' mode choice by exploring the role of the “perceived importance” of the most relevant service dimensions in determining the attractiveness of two alternatives to “all-road” transport: logistics terminals and road–sea intermodal services. This is carried out through a revealed/stated preference experiment and a mixture of logit framework. Our results support the hypothesis that operators' attitudes towards time, punctuality and risk of loss/damage can significantly enhance the explanatory power of the choice model, thus providing useful information for policy-makers to improve the regional freight mobility system. The “all road” option is preferred by hauliers concerned with the risk of loss/damage but it is, instead, disregarded by those assigning great relevance to punctuality. We also found substantial heterogeneity among respondents: larger firms tend to assign a lower value to time but a higher importance to the risk of loss/damage, especially if shipments are not frequent. In addition, the relevance of service reliability is higher the reliability greater the load size. Finally, we find that the nature of the transported goods significantly influences the choices of operators: when consigning perishables, hauliers tend to prefer the flexibility of a road-related mode. Any policy aiming at fostering the growth of intermodal transport and logistics and to remove obstacles to implementing rationalisation policies in the field of freight transport should take account of these elements.

Accommodating Risk Attitudes in Freight Transport Behaviour Research

Behavioural choice modelling is growing in interest as a framework to understand the decision-making of shippers, freight forwarders and other freight agents. Since the 1980s, we have witnessed an increasing number of freight behaviour studies, primarily the freight mode choice, where the roles of one or more freight decision-makers has been addressed, which was neglected in the traditional aggregate approach to freight demand modelling. Stated preference techniques have become a main approach to establishing the role of attributes that define the key drivers in the freight distribution chain. The underlying theory of choice is based on the neoclassical economic assumption that a decision-maker, in choosing, acts as if they are a utility maximizer (working to deliver a profit maximization or cost minimization outcome for the freight business), and this utility maximizing behaviour engenders a population theory of Random Utility Maximization (RUM). Despite the continuing appeal of the RUM framework in applied travel choice studies, a number of specific application assumptions have been questioned by studies in psychology and behavioural economics, arguing that the decisions made by agents are often conditioned on a number of underlying psychological components, one of which is risk attitude. This paper reviews recent freight behaviour studies established on RUM, and presents a major limitation of adopting a risk-neutral assumption through its linear utility specification. Using an existing freight stated choice data set, a nonlinear utility model is estimated which reveals risk-taking attitudes of transporters and shippers. An alternative behavioural paradigm, Rank-Dependent Utility Theory (RDUT), is introduced and incorporated to better accommodate trip time variability, a feature of growing importance in transport systems (passenger and freight). The proposed attribute-specific extended RDUT framework that accommodates the attitude towards risk and preference in freight transport behaviour modelling requires new data, which we detail.

A Commodity Distribution Model for a Multi-Agent Freight System

Modeling transportation systems at the microscopic level is currently gaining favor among researchers throughout the world. A multi-agent system, which is one method of microscopic modeling, is a dynamic framework dealing with the behavior of each individual actor in the transport system, and is especially favored for passenger transport models. Likewise, freight systems need a similar framework to better represent the interactions amongst freight agents, as large numbers of heterogeneous freight actors and other factors are involved. This paper proposes an extension of a multi-agent transport modeling system to cover the area of freight movement. The focus of this paper is at the stage of commodity distribution, in order to model the links between suppliers and receivers of commodities. The model is developed based on the principal of commodity movement through supply chains. The structure is a demand derived model, where receivers are the decision makers who choose their suppliers. The model is constructed based on the discrete choice method, considering the constraints of the amount of the commodity generated and the amount desired by each of the companies, travel impedance and attractive factors of the shippers. The model is developed and applied to the movement of urban freight in the Tokyo Metropolitan Area.

내륙컨테이너운송체계에 대한 선호도 분석 - 부산지역 업체들을 대상으로 -

The cost of domestic container transportation is higher than international sea transportation and it cannot meet the needs of customers either. However, domestic carriers try hardly nothing to improve the carriage system. Especially, the inland transportation connecting Busan port is not receiving a careful study in spite of the importance and urgency now. This paper reviews intention of forwarders, shipping companies, and transport companies conducting a questionnaire and analyse the preferences of transportation modes amongst existing highway, railway, coastal shipping and inland waterway. Its aim is to analyse which factors affect freight agents to choose particular mode.

Commodity Distribution Model Incorporating Spatial Interactions for Urban Freight Movement

The commodity distribution model proposed in this paper is developed in such a way that the movement of commodities is explained as an outcome of their flow through several freight agents in a supply chain. As commodity flow is fundamentally determined by demand, the proposed model was developed from a discrete choice model that considered the individual behavior of a customer to decide the suppliers from which to purchase and the amount of commodity to acquire from each of them. The model not only takes into account the interplay between shipper and customer in a supply chain but also captures the spatial interactions among alternatives and among customers, because spatial effects generally affect customer preference. In this study, several model specifications were developed and compared, with and without incorporating spatial interactions. The empirical results of the model, which were applied to analyze the urban commodity distribution in the Tokyo metropolitan area, indicate that integrating both spatial interactions among alternatives and among customers statistically improves the model's performance.

Commodity Distribution Model Incorporating Spatial Interactions for Urban Freight Movement

The commodity distribution model proposed in this paper is developed in such a way that the movement of commodities is explained as an outcome of their flow through several freight agents in a supply chain. As commodity flow is fundamentally determined by demand, the proposed model was developed from a discrete choice model that considered the individual behavior of a customer to decide the suppliers from which to purchase and the amount of commodity to acquire from each of them. The model not only takes into account the interplay between shipper and customer in a supply chain but also captures the spatial interactions among alternatives and among customers, because spatial effects generally affect customer preference. In this study, several model specifications were developed and compared, with and without incorporating spatial interactions. The empirical results of the model, which were applied to analyze the urban commodity distribution in the Tokyo metropolitan area, indicate that integrating both spa...

SUPPLY CHAIN SIMULATION FOR MODELING THE INTERACTIONS IN FREIGHT MOVEMENT

Abstract: Freight movement is a dynamic process involving with complex interaction among many agents by which the commodities are flowed through supply chains. Simulation based model allows such dynamic and complex interaction system to be undertaken. Simulation based multi-agent approach is therefore utilized to model the behaviors of agents and their interactions in supply chains in order that the mechanism of freight movement is better demonstrated. This model simulates day-to-day activities of agents (including, retailers, manufacturers, and suppliers) in product acquisition, production, and distribution. Systematic framework of the proposed model permits wide variety of application. Feedback and learning of freight agents and variation in freight traffic demand can be captured by the proposed model. This paper discusses the on-going research of supply chain simulation and provides the modeling framework, mathematical formulation, and the application of the model to the supply chain of food industry in the Tokyo Metropolitan Area.

International Airports as Growth Poles: A Case Study of Heathrow Airport

International Airports as Growth Poles: A Case Study of Heathrow Airport