How to Improve the Capture of Urban Goods Movement Data?

The surveys specifically focused on the thorough knowledge of urban freight transport appeared about ten years ago. The local problematic of goods transport at local level was partially taken into account by the city planners and by the researchers: until recent years, the integration of goods transport in the total urban flows models was estimated applying a multiplying factor to car traffic. Delivering goods was not considered like a concern.Because of the quick growth of car traffic in the cities, the main stakes changed too: the fight against traffic congestion, the management of the lack of space (shipment consolidation and storage), the attempts to reduce local environmental impacts and global externalities (energy saving, reduction of greenhouse gas emissions), and economic valuation of city centres (under the pressure of a slowed down economic growth).All these changes were taking place in a context in which available rooms for manoeuvre were limited by factors such as congestion, concerns about the quality of urban life and budget restriction. It resulted in a growing unease on the freight transport industry and the city authorities, the latter having little or no data, methods and references in order to elaborate a satisfactory policy framework.surveys on urban freight transport ; urban freight movements ; urban freight data collection ; urban goods data collection ; diversity of measurement units and methods ; state of the art

Analysis and operational challenges of dynamic ride sharing demand responsive transportation models

There is a wide body of evidence that suggests sustainable mobility is not only a technological question, but that automotive technology will be a part of the solution in becoming a necessary albeit insufficient condition. Sufficiency is emerging as a paradigm shift from car ownership to vehicle usage, which is a consequence of socio-economic changes. Information and Communication Technologies (ICT) now make it possible for a user to access a mobility service to go anywhere at any time. Among the many emerging mobility services, Multiple Passenger Ridesharing and its variants look the most promising. However, challenges arise in implementing these systems while accounting specifically for time dependencies and time windows that reflect users’ needs, specifically in terms of real-time fleet dispatching and dynamic route calculation. On the other hand, we must consider the feasibility and impact analysis of the many factors influencing the behavior of the system – as, for example, service demand, the size of the service fleet, the capacity of the shared vehicles and whether the time window requirements are soft or tight. This paper analyzes - a Decision Support System that computes solutions with ad hoc heuristics applied to variants of Pick Up and Delivery Problems with Time Windows, as well as to Feasibility and Profitability criteria rooted in Dynamic Insertion Heuristics. To evaluate the applications, a Simulation Framework is proposed. It is based on a microscopic simulation model that emulates real-time traffic conditions and a real traffic information system. It also interacts with the Decision Support System by feeding it with the required data for making decisions in the simulation that emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The obtained results prove the potential feasibility of the mobility concept.Postprint (published version

Drivers and Impacts of R&D Adoption on Transport and Logistics Services

Actually, technologies and applications in industries are changing via business restructuring, new business models, new knowledge and supply chains. So R&D is not focused primarily on manufacturing industry as it used to be, but on different kinds of industries as logistics and transport (TLS). Nevertheless, the characteristics of the TLS industry determine the introduction of specific R&D solutions accordingly to sectors operations. The objective of this paper is to describe the R&D opportunities in the TLS industry and how managers use them to make their businesses more innovative and efficient. Using the Structure-Conduct-Performance (SCP) model the paper identifies the links between R&D adoption and innovation dynamics. Relating the findings, on the driver’s side there are three points that are worth mentioning: increasing market competition, the relationships of firms interacting with each other and the availability and quality of complementary assets such as employee skills and IT know-how. On the impacts’ side, firms advanced in terms of implementing R&D solutions are more likely to implement organizational changes. Finally, a set of recommendations on how to further improve the continuous innovation in the TLS industry is presented

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

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. Keywords: freight transport; city logistics; commodity flow; freight tours; simulation; AB

Algorithms for bundling and pricing trucking services: Deterministic and stochastic approaches

Bundling and pricing trucking services is an important strategic decision for carriers. This is helpful when they consider the incorporation of new businesses to their networks, look for economic and optimal operations, and develop revenue management strategies. Reverse combinatorial auctions for trucking services are real-world examples that illustrate the necessity of such strategies. In these auctions, a shipper asks carriers for quotes to serve combinations of lanes and the carriers have to bundle demand and price it properly. This dissertation explores several dimensions of the problem employing state-of-the-art analytical tools. These dimensions include: Truckload (TL) and less-than-truckload (LTL) operations, behavioral attributes driving the selection of trucking services, and consideration of deterministic and stochastic demand. Analytical tools include: advanced econometrics, network modeling, statistical network analysis, combinatorial optimization, and stochastic optimization. The dissertation is organized as follows. Chapter 1 introduces the problem and related concepts. Chapter 2 studies the attributes driving the selection of trucking services and proposes an econometric model to quantify the shipper willingness to pay using data from a discrete choice experiment. Chapter 3 proposes an algorithm for demand clustering in freight logistics networks using historical data from TL carriers. Chapter 4 develops an algorithmic approach for pricing and demand segmentation of bundles in TL combinatorial auctions. Chapter 5 expands the latter framework to consider stochastic demand. Chapter 6 uses an analytical approach to demonstrate the benefits of in-vehicle consolidation for LTL carriers. Finally, Chapter 7 proposes an algorithm for pricing and demand segmentation of bundles in LTL combinatorial auctions that accounts for stochastic demand. This research provides meaningful negotiation guidance for shippers and carriers, which is supported by quantitative methods. Likewise, numerical experiments demonstrate the benefits and efficiencies of the proposed algorithms, which are transportation modeling contributions

New Concept of Container Allocation at the National Level: Case Study of Export Industry in Thailand

This paper presents container allocation technique of which minimizing the total opportunity loss of an export industry in Thailand. This new allocation concept applies as a strategic management tools at the national level since it is consistent to the characteristics of the container supply chain management in Thailand. The first section of this paper presents the review of facts and problems of container supply chain management. It reveals that containerization system is significant to the international trade as it holds good characteristics of sea transportation. It can transport a lot of products while minimize the damage of goods. Supply chain management of the containerization system presents and shows that there are four main players in managing the container – principal, port, container depot, and customer. After an intensive review of containerization system’s problem, the most common problem that all parties have encountered is an imbalance between demand and supply of container. The well-known solution to the stated problem is relocation of containers between various places using optimization technique, which aims to minimize operation cost. Indeed, those solutions are unable solve the containerization system’s problem in Thailand: lacking their own fleets: having no bargaining power in relocating container between areas as needed. In the present, many of Thai exporters face with losses of sales or profit because they cannot find enough or proper containers to transport their goods to the customer. The authors, therefore, have seen that those problems need to be strategically solved by the government. The limited number of containers must be properly allocated to the exporter with regard to the minimum losses to the economics of the country. The main contributions of this paper are two folds. First, the opportunity losses of the various export industry are indicated when lack of containers, Second, the mathematical model has been formulated using linear programming technique with several constraints, such as, demand, supply, obsolete time, operating cost, lead time etc. The authors hope that the new concept presented in this paper will provide the great contribution for other countries, which face the same problem of Thailand. Keywords: Container Management, Opportunity Loss, Allocation Problem, Optimization, International Trad

Recent Trends and Innovations in Modelling City Logistics

AbstractThere are many challenges associated with moving goods within cities as urban areas become larger and elderly residents require more healthcare in their homes. Air quality is also impacted by urban freight vehicles. This paper presents a review of recent trends and innovations in modelling city logistics. New techniques for modelling city logistics developed in the areas of emissions, healthcare and mega-cities are outlined. This paper describes the formulation, solution methodologies and applications of these models

Sustainable Freight Transport

This Special Issue of Sustainability reports on recent research aiming to make the freight transport sector more sustainable. The sector faces significant challenges in different domains of sustainability, including the reduction of greenhouse gas emissions and the management of health and safety impacts. In particular, the intention to decarbonise the sector’s activities has led to a strong increase in research efforts—this is also the main focus of the Special Issue. Sustainable freight transport operations represent a significant challenge with multiple technical, operational, and political aspects. The design, testing, and implementation of interventions require multi-disciplinary, multi-country research. Promising interventions are not limited to introducing new transport technologies, but also include changes in framework conditions for transport, in terms of production and logistics processes. Due to the uncertainty of impacts, the number of stakeholders, and the difficulty of optimizing across actors, understanding the impacts of these measures is not a trivial problem. Therefore, research is not only needed on the design and evaluation of individual interventions, but also on the approach of their joint deployment through a concerted public/private programme. This Special Issue addresses both dimensions, in two distinct groups of papers—the programming of interventions and the individual sustainability measures themselves

Global and International Logistics

This book contains 10 reviewed papers published as a Special Issue “Global and International Logistics” in the journal Sustainability, edited by Prof. Dr. Ryuichi Shibasaki, Prof. Dr. Daisuke Watanabe, and Dr. Tomoya Kawasaki. The topics of the papers contain the impact of logistics development under the China’s Belt and Road initiative (BRI) by using the improved gravity model, strategies against barriers to the BRI from a logistics and supply chain management perspective, the dynamic interaction between international logistics, and cross-border e-commerce trade, the effect of China’s restrictive programs on the international trade of waste products, the empty container repositioning problem of shipping companies with foldable containers, port capacity and connectivity improvement in the hub and feeder network in Indonesia, GHG emission scenarios for the maritime shipping sector using system dynamics, incorporating a shipping and shipbuilding market model, the emission inventory and bunker consumption from a LNG fleet from an automatic identification system database, the factors that can help select between land transport and maritime shipping in long-distance inter-regional cross-border transport, and container transport simulations in Myanmar with the global logistics intermodal network assignment model including both maritime shipping and land transport in the land-based Southeast Asia region. Some papers are related to the 8th International Conference on Transportation and Logistics (T-LOG 2020) which was held online on 6–7 September 2020 hosted by Universitas Internasional Semen Indonesia