Search results

The purpose of this paper is to investigate the application of the dynamic vehicle routing problem for last mile distribution during disaster response. The authors explore a model that involves limited heterogeneous vehicles, multiple trips, locations with different accessibilities, uncertain demands, and anticipating new locations that are expected to build responsive last mile distribution systems.

The modified simulated annealing algorithm with variable neighborhood search for local search is used to solve the last mile distribution model based on the criterion of total travel time. A dynamic simulator that accommodates new requests from demand nodes and a sample average estimator was added to the framework to deal with the stochastic and dynamicity of the problem.

This study illustrates some practical complexities in last mile distribution during disaster response and shows the benefits of flexible vehicle routing by considering stochastic and dynamic situations.

This study only focuses day-to-day distribution on road/land transportation for distribution, and additional transportation modes need to be considered further.

The proposed model offers operational insights for government disaster agencies by highlighting the dynamic model concept for supporting relief distribution decisions. The result suggests that different characteristics and complexities of affected areas might require different distribution strategies.

This study modifies the concept of the truck and trailer routing problem to model locations with different accessibilities while anticipating the information gap for demand size and locations. The results show the importance of flexible distribution systems during a disaster for minimizing the disaster risks.

To propose an improved algorithm for the state estimation of distribution networks based on the unscented Kalman filter (IUKF). The performance comparison of unscented Kalman filter (UKF) and newly developed algorithm, termed Improved unscented Kalman Filter (IUKF) for IEEE-30, 33 and 69-bus radial distribution networks for load variations and bad data for two measurement noise scenarios, i.e. 30 and 50 per cent are shown.

State estimation (SE) plays an instrumental role in realizing smart grid features like distribution automation (DA), enhanced distribution generation (DG) penetration and demand response (DR). Implementation of DA requires robust, accurate and computationally efficient dynamic SE techniques that can capture the fast changing dynamics of distribution systems more effectively. In this paper, the UKF is improved by changing the way the state covariance matrix is calculated, to enhance its robustness and accuracy under noisy measurement conditions. UKF and proposed IUKF are compared under the cummulative effect of load variations and bad data based on various statistical metrics such as Maximum Absolute Deviation (MAD), Maximum Absolute Per cent Error (MAPE), Root Mean Square Error (RMSE) and Overall Performance Index (J) for three radial distribution networks. All the simulations are performed in MATLAB 2014b environment running on an hp core i5 laptop with 4GB memory and 2.6 GHz processor.

An Improved Unscented Kalman Filter Algorithm (IUKF) is developed for distribution network state estimation. The developed IUKF is used to predict network states (voltage magnitude and angle at all buses) and measurements (source voltage magnitude, line power flows and bus injections) in the presence of load variations and bad data. The statistical performance of the coventional UKF and the proposed IUKF is carried out for a variety of simulation scenarios for IEEE-30, 33 and 69 bus radial distribution systems. The IUKF demonstrated superiority in terms of: RMSE; MAD; MAPE; and overall performance index J for two measurement noise scenarios (30 and 50 per cent). Moreover, it is shown that for a measurement noise of 50 per cent and above, UKF fails while IUKF performs.

UKF shows degraded performance under high measurement noise and fails in some cases. The proposed IUKF is shown to outperform the UKF in all the simulated scenarios. Moreover, this work is novel and has justified improvement in the robustness of the conventional UKF algorithm.

On one side, the purpose of this paper is to numerically analyze the emergency order allocation mechanism and help managers to understand the relationship between the emergency coefficient, uncertainty and emergency cost in two‐echelon logistics service supply chain. On the other side, the purpose of this paper is to help managers understand how to deal with the problem of order allocation in the two‐echelon logistics service supply chain better in the case of emergency.

The paper presents a multi‐objective planning model for emergency order allocation and then uses numerical methods with LINGO 8.0 software to identify the model's properties. The application of the order allocation model is then presented by means of a case study.

With the augment of uncertainty, the general cost of logistics service integrator (LSI) is increasing, while the total satisfaction of all functional logistics service providers (FLSPs) is decreasing, as well as the capacity reliability; at the same time the emergency cost coefficient is closely correlative with the satisfaction and general penalty intensity of FLSPs; finally, the larger the emergency cost coefficient is, the more satisfaction of FLSPs, but the capacity reliability goes up first and down later.

Management should note that it is not better when emergency cost coefficient is bigger. The general satisfaction degree of FLSP increases with the augment of emergency cost coefficient, but there is an upper limit of the value, i.e. it will not increase indefinitely with the augment of emergency cost coefficient. This paper also has some limitations. The optional emergency cost coefficient only adopted a group of data to analyze while the trend of the reliability of logistics capacity needs to be further discussed. In addition, the algorithm of emergency order allocation model in the case of multi‐objective remains to be solved.

Under emergency conditions, LSIs can adopt this kind of model to manage their FLSPs to obtain the higher logistics performance. But LSIs should be careful selecting emergency cost coefficient. In accordance with different degrees of emergency logistics demand, LSIs can determine reasonable emergency cost coefficient, but not the bigger, the better, on the premise that LSIs acquire maximum capacity guarantee degree and overall satisfaction degree of FLSPs. FLSPs can make contract bargaining of reasonable emergency coefficient with LSIs to make both sides get the best returns and realize the benefit balance.

Many studies have emphasized the capacity allocation of manufactures, order allocation of manufacturing supply chain and scheduling model of emergency resources without monographic study of supply chain order allocation of logistics service. Because the satisfaction degree of FLSPs the cost of integrators needs to be considered in the process of order allocation, and the inventory cost of capacity does not exist, it is different from the issue of capacity allocation planning of manufacture supply chain. Meanwhile, the match of different kinds of logistics service capacity must be considered for the reason of the integrated feature of logistics service. Additionally, cost is not the most important decision objective because of the characteristics of demand uncertainty and weak economy. Accordingly, this paper considers these issues.

The roles of ‘conventional’ (fixed-route and fixed-timetable) bus services is examined and compared to demand-responsive services, taking rural areas in England as the basis for comparison. It adopts a ‘rural’ definition of settlements under a population of 10,000.

Evidence from the National Travel Survey, technical press reports and academic work is brought together to examine the overall picture.

Inter-urban services between towns can provide a cost-effective way of serving rural areas where smaller settlements are suitably located. The cost structures of both fixed-route and demand-responsive services indicate that staff time and cost associated with vehicle provision are the main elements. Demand-responsive services may enable larger areas to be covered, to meet planning objectives of ensuring a minimum of level of service, but experience often shows high unit cost and public expenditure per passenger trip. Economic evaluation indicates user benefits per passenger trip of similar magnitude to existing average public expenditure per trip on fixed-route services. Considerable scope exists for improvements to conventional services through better marketing and service reliability.

The main issue in England is the level of funding for rural services in general, and the importance attached to serving those without access to cars in such areas.

The boundary between fixed-route and demand-responsive operation may lie at relatively low population densities.

The chapter uses statistical data, academic research and operator experience of enhanced conventional bus services to provide a synthesis of outcomes in rural areas.

Evolvable production systems enable fully reconfiguration capabilities on the shop floor through process‐oriented modularity and multi‐agent‐based distributed control. To be able to benefit architectural and operational characteristics of evolvable systems, there is a need of a new planning approach which links shop floor characteristics and planning operations. This paper seeks to address these issues.

Evolvable production system has a structured methodology in itself. Consistent to this, a reference planning architecture is developed aiming to achieve agility on planning activities. Besides a workload control method is proposed and implemented as a part of the planning architecture.

First applications of evolvable systems have been implemented through European research projects. Shop floor working principles and architectural characteristics are consistent to facilitate more agility on planning activities which are framed at a planning reference architecture called demand responsive planning. As an implementation case, an agent‐based workload control method is proposed and implemented. The characteristics of EPS and proposed planning architecture enable continuous and dynamic workload control of the shop floor to be implemented.

This paper presents a new planning model compatible with evolvable production systems targeting to agility to demand on planning and control activities benefiting shop floor enhancements of a fully reconfigurable system which enables to relax constraints imposed from production systems to planning. In addition, a continuous and dynamic workload control method is proposed and implemented.

To offer knowledge about the global development of large-scale demand responsive transport systems (DRT), and to stimulate dialogue and collaboration for further innovation and improvement of these systems.

A review of the literature shows how DRT has evolved from the first applications in the 1970s to very complex operations in the last two decades with hundreds of vehicles and thousands of passengers every day. Data collection from available sources on the Internet and personal communications during international projects, conferences, and networking are used to quantify the development and status for large-scale DRT.

In the last decade, DRT is moving slowly ahead with real progress in some countries. The “Danish Model” is a good example of how to organize DRT for the best possible coordination of different mobility services, both “open” to the general market and for the special needs market. Such integration is also observed in a few places in the United States, and some European countries. For a real progress there is a great need and potential for international collaboration, as has been the case for most other sectors.

This is the first known attempt to collect information and compile a list of the 30 largest DRT systems in the world. This is used to analyze trends and provide insight into new directions for large-scale DRT systems. Suggestions for collaboration in various aspects of DRT should be valuable to organizations and policy makers with interest and power to further DRT innovations and operations.

An increasing literature focuses on how Demand Responsive Transport (DRT) may contribute to improve public transport. However, qualitative studies about whether such services contribute to social inclusion are lacking. The aim is therefore to understand how citizens experience DRT services.

For this purpose, we compare the different local public transport solutions in three rural municipalities in Norway. One case represents a conventional public transport service with a school bus that is open for all. The two other cases represent DRT solutions with different characteristics in terms of how extensive the services are. The data are qualitative, gathered via interviews and focus groups.

We find that who the users are and their patterns of use differ between the cases. The more extensive the service is, the more popular it is – even to the extent that leisure clubs adapt their start and end times to the public transport routes. Moreover, the evidence suggests that door-to-door transport is crucial for the ability of many people of older age to travel.

The need for door-to-door services means that flexibility has to be incorporated into DRT schemes with fixed bus stops, if the aim is to cover all citizens.

The insights about how not only the users themselves experience different transport services, but also their relations, provide added value. Finally, we argue that, given among others the dispersion of transport responsibilities on different political levels and sectors, the DRT services have not been successful in solving efficiency issues.

This chapter provides the context for this book and highlights how the different chapters contribute to a greater understanding of how the flexible transport future may emerge.

This chapter reviews the content of the book, drawing together the threads to provide insights into the important issues and policies around the world both in practice and for the future.

This book benefits from the papers presented at the TRB-sponsored International Paratransit Conference, “Shaping the New Future of Paratransit,” held in Monterey, CA in the United States (US) in October 2014. Over and above this, chapters were commissioned so as to provide a broader understanding of context and operations. The present is affected by the common problem of the silo nature of funding for transport and the need for innovative solutions to develop partnership working and business models which in turn will allow paratransit or flexible transport systems (FTS) to flourish. This chapter also points to the considerable contribution of the chapters which look to the flexible transport future. These detail the way in which our understanding of mobility must change, the role of technology as an enabler, and the way in which automation will change each mobility mode and the connections between them.

This chapter offers a multidimensional perspective of the current status, operational aspects, and a wealth of case study material to underpin policy and practice in paratransit or FTS. Its particular value is centered on providing not only practice-focused policy content but research content which postulates how the flexible future may need to be influenced to emerge in a way to add to sustainability.