دانلود مقاله ISI انگلیسی شماره 6921
عنوان فارسی مقاله

سیستم های هوشمند حمل و نقل باری : بررسی و نقش تحقیق در عملیات

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
6921 2009 17 صفحه PDF سفارش دهید 12860 کلمه
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عنوان انگلیسی
Intelligent freight-transportation systems: Assessment and the contribution of operations research
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Transportation Research Part C: Emerging Technologies, Volume 17, Issue 6, December 2009, Pages 541–557

کلمات کلیدی
- سیستم های حمل و نقل هوشمند - حمل و نقل باری - تدارکات شهر - تجارت الکترونیک
پیش نمایش مقاله
پیش نمایش مقاله سیستم های هوشمند حمل و نقل باری : بررسی و نقش تحقیق در عملیات

چکیده انگلیسی

While it is certainly too early to make a definitive assessment of the effectiveness of Intelligent Transportation Systems (ITS), it is not to take stock of what has been achieved and to think about what could be achieved in the near future. In our opinion, ITS developments have been up to now largely hardware-driven and have led to the introduction of many sophisticated technologies in the transportation arena, while the development of the software component of ITS, models and decision-support systems in particular, is lagging behind. To reach the full potential of ITS, one must thus address the challenge of making the most intelligent usage possible of the hardware that is being deployed and the huge wealth of data it provides. We believe that transportation planning and management disciplines, operations research in particular, have a key role to play with respect to this challenge. The paper focuses on Freight ITS: Commercial Vehicle Operations and Advanced Fleet Management Systems, City Logistics, and electronic business. The paper reviews main issues, technological challenges, and achievements, and illustrates how the introduction of better operations research-based decision-support software could very significantly improve the ultimate performance of Freight ITS.

مقدمه انگلیسی

The term Intelligent Transportation Systems, or ITS, is generally used to refer to tomorrow’s technology, infrastructure, and services, as well as the planning, operation, and control methods to be used for the transportation of persons and freight. With ITS, however, tomorrow is already here. The initial driving force for the development of ITS has been the realisation that further infrastructure construction could no longer be the only answer to address the increase in transportation demand and the various problems that it inevitably creates. The obvious answer to the need to significantly increase the capacity of transportation systems was to try to make them more efficient through an integrated use of the latest developments in various areas, infrastructure and vehicle technologies, electronics, telecommunications, computing hardware, positioning systems, as well as advanced data processing and sophisticated planning and operation methods. Over the last 15 years or so, one has thus witnessed tremendous efforts aimed at creating and deploying a new generation of transportation systems that aim to control congestion, increase safety, increase mobility, and enhance the productivity and effectiveness of private and public fleets. In the beginning, ITS research, development, and investment focused on urban automobile transportation and a totally public organisational structure and management. It has now evolved to include all types and levels of transportation, persons as well as freight, for which private industries offer a variety of extended, adapted and targeted services. Tremendous challenges and opportunities exist for ITS research, development, and business, particularly so in the area of freight transportation that, until recently, appeared relatively less prominently on the agenda of ITS stakeholders. Indeed, the development of Freight ITS and the evolution of the freight-transportation industry are closely related, particularly relative to the use of information and decision technologies in response to the tremendous shift in commercial and industrial practices of the last decade. This is in stark contrast to most other ITS areas, where the needs of people mobility in congested urban centers constitute the overwhelming driving force. While it is certainly too early to make a definitive assessment of the effectiveness of ITS, it is not to take stock of what has been achieved and, more importantly, to think about what could be achieved in the near future. In our opinion, ITS developments have been up to now largely hardware-driven, and have led to the introduction of many sophisticated technologies in the transportation arena. We are thus now, among other things, in the position to collect enormous amounts of data about the current state and the operations of transportation systems, and to transmit rapidly these data, in one form or the other, to transportation authorities, carriers, and travellers. Two critical questions remain though: are all of these data transformed into useful information? And, is this information properly exploited? The correct answer to both of these questions is clearly negative. The reason for this situation is that the development of the software component of ITS, models, decision-support systems, and so on, has been dramatically lagging behind that of its hardware component. In many cases, very detailed data are still processed and acted upon by the human operators with very few decision-support tools, if at all. In a sense, we are now faced with a challenge similar to the one that led to the initial development of ITS, that is, to make the best, the most intelligent usage possible of all that wonderful hardware that is being deployed. We believe that transportation planning and management disciplines, and in particular operations research, have a key role to play with respect to this challenge. Challenges for the freight-transportation industry result from the major changes affecting supply chains and logistical processes in trade and commerce. The first factor is the strong impetus toward inventory reduction that led to the “Just-in-Time” procurement practices and, more recently, to just-in-time replenishments of goods in the retail industry. The globalization and liberalization of markets and the creation of free trade zones constitute the second major changing factor. The restructuring of manufacturing and distribution channels worldwide has accompanied the globalization of the economy. Production units are re-located, and the components required for the final assembly of complex industrial products are often brought in from many distant locations. Continuously increasing volumes of industrial, commercial, and consumer goods are imported into Europe and North America and transported over long distances from the so-called emerging-economy countries, e.g., China, India, and Brazil. All the while, trans-national centralized warehousing facilities and value-added distribution centers are changing the flow of goods almost everywhere. The development of Internet-based electronic business is also strongly contributing to the transformation of the freight-transportation industry. The main external factors driving this transformation are the modifications to the logistic chains and practices of major industries and economic sectors, the proliferation of electronic spaces (websites) where shippers and carriers may meet and close deals, and the continuously increasing volume of individual consumer e-commerce activities. These changes have certainly resulted in higher demand for transportation. They have also increased the requirements for freight-transportation services in terms of enhanced customer value: reduce transportation and distribution costs, while responding to the customer needs in terms of delivery time and reliability. Moreover, events such as 9/11, the war on terrorism, and the war on drugs have created potential impediments to the flow of goods due to safety and security threats that can only be mitigated through the use of technology and increased efficiency. Last but not the least, environmental and energy concerns are taking center stage. Indeed, the transportation sector is responsible of a significant amount of greenhouse gas emissions: 13% of all emissions of greenhouse gases and 23% of world CO2 emissions from fossil fuel combustion (ITF, 2008). The last measure stands at 30% in countries of the Organisation for Economic Co-operation and Development (ITF, 2008) and was 27% in the United States in 2003 (EPA, 2006). It is estimated that the freight transportation contributes roughly a third of the CO2 emissions of the world transport sector (ITF, 2008). This distribution is uneven, however, being worse in large cities, for example. Thus, a report by the Organisation for Economic Co-operation and Development (OECD, 2003) assigns 43% of sulphur and 61% of particulate matter emissions in London to freight transportation, while for nitrogen oxides emissions, the figures are 28% for London, 50% for Prague, and 77% for Tokyo. These contributions are growing and are expected to continue to grow with the increase in the freight-transportation activity and the corresponding consumption of fossil fuels. The impact on the freight transportation and logistics sector comes both from the initiatives to control, hopefully reduce, emissions and environmental impacts (e.g., vehicle emission legislation and environmental and congestion road pricing) and from the increases in the cost of energy. These factors have put, and continue to put, tremendous pressure on the freight carriers and the managers of intermodal facilities to reduce and control costs, to plan and operate efficient, timely, and reliable services, and to react rapidly to new customer requests, emerging or shifting business opportunities, and changes in the economic and regulatory environment. The freight-transportation industry bases a significant part of the answer it offers to these challenges on information and decision technologies: two-way communication, location and tracking devices, electronic data interchange, advanced planning and operation decision-support systems, and so on. Intelligent Transportation Systems integrate and enhance these technologies within the firm, as well as through the linkages and exchanges between the firm and its environment (customers, partners, regulators, etc.). Moreover, the volatility of the stock exchange notwithstanding the trend of e-business development and utilization is clear and strong. This signals to transportation firms, as to other economic agents, that significant opportunities exist in terms of larger and stronger business partnerships, more streamlined, rapid, and demand-responsive decision processes, improved operations and service levels, enhanced customer satisfaction and, ultimately, profitability. To reap the benefits of these opportunities, freight carriers may take advantage of the convergence of ITS and e-business technologies and the possibility of integrated, advanced operations research-based planning and operation decision-support systems. The purpose of this paper is threefold: (1) to make an assessment of Freight ITS achievements; (2) to illustrate the convergence of Freight ITS and e-business technologies by focusing on electronic auctions; and (3) to show how the introduction of better decision-support software, based on operations research models and methods, could very significantly improve the ultimate performance of these systems. The paper is organized as follows. We first recall briefly the scope, components, and main enabling technologies of Freight ITS. The next sections are dedicated, respectively, to Commercial Vehicle Operations, Advanced Fleet Management Systems, City Logistics, and a brief exploration of linkages between Freight ITS and e-business. We conclude with a number of perspectives and research and development challenges.

نتیجه گیری انگلیسی

This paper aims to assess ITS achievements with respect to the transportation of freight and to identify challenges, opportunities, and promising research and development directions. We examined the Freight ITS field from several complementary points of view: enabling technologies including Electronic Data Interchange, Commercial Vehicle Operations including border-crossing issues, Advanced Fleet Management Systems, the City Logistics concept for integrated urban freight management, and the links and convergence of Freight ITS and e-business. Throughout the presentation, we attempted to illustrate how the introduction of better decision-support software may very significantly improve the ultimate performance of Intelligent Freight-Transportation Systems. Similar to many other ITS areas, Freight ITS development proceeds along three major, parallel but complementary, directions. The first concerns vehicular and infrastructure developments. The second direction concerns the electronics, location, tracking, and communication hardware, as well as the associated information-technology software. The third targets the methodologies – models and algorithms – required to process the data and transform it into timely and meaningful information and intelligent advice for advanced system and fleet planning, as well as management, operations, and control systems. The ultimate performance and long-term success of ITS depends on a balanced and harmonious integration of these aspects. It appears, however, that governments and industry privileged up to now the hardware aspect to the detriment of the methodological one. In many cases, data provided by very sophisticated devices and relayed through advanced communication technologies are still being processed and acted upon by the human operators with little, if any, decision-support tools. There is thus a challenge to drastically increase the intelligence of ITS. The various applications described in this paper illustrate the key role operations research models and methods play in the analysis of ITS needs and projects, as well as in the development of the software component of ITS. Such methodologies transform the huge amount of data provided by ITS technologies into useful information that may be either distributed to the various ITS users or transformed into operating policies and instructions. Operations research-based data processing and decision-support systems may explore and evaluate the behaviour of the transportation system under various conditions and develop contingency plans, predict the state of the system over the next time periods, generate general or user-tailored itineraries or guidance instructions, plan operations and assist the real-time management of fleets. Many challenges and opportunities for research and development may still be identified, however. An important research field that should be explored addresses the exchanges and integration of Freight ITS deployed at border crossings and ports, the Advanced Traffic Management and Advanced Traveller Information Systems of the corresponding cities and regions, and the AFMS of the shippers and carriers that use the systems. This involves not only the integration of electronics and communication systems, but also those of the planning and scheduling activities. Being pre-approved means nothing if one must still wait for hours together with other pre-approved vehicles because everybody desires to cross simultaneously. This field belongs to the broader research domain focusing on the issues related to the management of ITS and of security-equipped borders and ports. The efficiency of these facilities is tributary of their design and management methods and processes. The whole field is not yet sufficiently addressed, and the operations research community may make a significant contribution. Research and development efforts are currently under way in several AFMS areas. The methodological developments of recent years in the various fields of operations research, combined to recent advances in computer science, in particular in parallel and distributed computing, put the required models and methods within our reach. More efforts are still needed, however, in particular relative to the real-time allocation of resources and management of operations, including real-time fleet management and vehicle re-routing. The issues are different but equally challenging whether urban or interurban transportation is considered, or whether the real-time decisions depend on the congestion and demand conditions only, or must account for and coordinate with the decisions of other agents (e.g., customs or port operations). The determination of appropriate trade-offs between accuracy of results and response time in real-time settings constitutes a particularly challenging issue in these contexts. Challenging research issues are also related to the development of the next generation of planning models and methods for carrier or shipper operations that reflect the new technologies and operating policies of carriers and integrate the stochastic and dynamic aspects of ITS. Equally challenging are the issues related to the planning and management of integrated logistics networks within the context of ITS, carrier AFMS, and e-business practices. In both cases, one must address the representation of the characteristics and behaviour of particular system components (e.g., terminals or cooperating firms) within an integrated planning model of the overall system. Identifying the “correct” trade-off among the accuracy of the component and system representations, the difficulty of the corresponding formulation, and the efficiency of solution methods is a particularly challenging issue, as is the representation of operational uncertainty into medium and long-term planning models and decision-support systems. City Logistics – the integrated management of freight movements within urban areas – constitutes a fascinating and quite young research domain. City Logistics brings new concepts, environments, and challenges to freight transportation. Operations research models and methods are needed to address these challenges and to assist the design, evaluation, planning, and real-time management of operations of City Logistics systems. All problems and applications mentioned in this paper require modelling efforts and the development of appropriate solution methods. Regarding the former, of particular relevance is the need to focus not only on the physical components of the systems considered and the associated flows of physical resources, but also on the adequate representation of the associated information and decision flows. Of particular interest with respect to the latter is the ability to address large instances of formulations including integer-valued decision variables, nonlinear objective functions and constraints, and uncertain data. The computational efficiency of our solution methods may be significantly enhanced through parallel and distributed computing. The integration of exact algorithms and meta-heuristics into co-operative search methods, and the development of co-operation mechanisms based on mathematical programming principles, decomposition methods in particular are promising research directions. A different research perspective is offered by the computing capabilities naturally distributed in ITS. Answering questions like “what is the correct arbitration between central processing and the utilisation of the computing power of local traffic controllers, on-board computers, and the next generation of transponder devices and how can one take advantage of these devices” will certainly prove challenging but may help addressing several issues in real-time Freight ITS operations. The “natural” technology-transfer instrument for operations research is the embedding of our models and methods into decision-support systems, which, directly or indirectly, are linked to the information-management system(s) of the firm. Several issues challenge our profession in this respect and we recall some of them here. Differences usually exist among the data in the information system, data required by the optimization, and the information that exists in the minds of human dispatchers and controllers. The latter communicate intensively with customers and equipment operators and base their decisions on a more nuanced status of the system, taking into account un-written traditions and preferences, as well as nuances in expressing instructions (e.g., “it would be nice to pick up this load before…”), than the one available to optimization. How much of this information can or should be automated? Given the amount which is not automated, how should the optimization models and the planning procedures be modified for best system-human integration and results? A related issue concerns the scope of the models we develop. Many research results address stylized problem settings, which are far from the complexity of problems in the field. The fact than many optimization-based systems are built to “assist” decision-making rather than directly “decide” is a partial answer to these issues. Only partial, however, and working on mode detailed models and solution methods that may be deployed and used in the field is one of the main challenges to our profession. The emergence and rapid growth of electronic business both challenges and offers freight carriers great opportunities for improved operations and profits. The convergence of information, communication, and decision technologies used in CVO and AFMS and in advisors for e-markets constitutes a significant advantage in this context. Significant research is still required in this area, however, in particular in order to develop efficient and comprehensive advisors. Three particularly challenging aspects of this issue are the (1) enhancement of the modeling capabilities and the efficiency of solution methods for the complex, stochastic and dynamic formulations related to identifying profitable bundles; (2) development of methodologies to address the contingency issues when bundles have to be negotiated in parallel or non-combinatorial markets; (3) determination of bidding strategies (e.g., estimation of probabilities of winning, of competitor behaviour, and price and bid modification) in various settings, parallel and continuous markets in particular. Strongly related to this is the area of coordination of various information sources, agents, and negotiations. Freight ITS change the way transportation activities are performed. This is exactly what is expected. On the other hand, however, freight vehicles interact with private and public vehicles carrying passengers. Moreover, Freight ITS, CVO systems for example, also interact strongly with logistics activities and industrial value chains. These impacts are not well understood, nor are the relations among ITS systems, environmental and sustainable development policies, and logistic chains. One lacks the knowledge and tools to evaluate and compare alternate systems, policies, and investments. One should be able to evaluate these interactions and the impact of Freight ITS on the general mobility within a given zone or on the logistic activities of particular industrial sectors. The development of such urban/regional planning systems, which reflect the utilization of CVO and AFMS technologies, require a multi-disciplinary effort: a thorough representation of the economic, operations, and information and decision technologies used by the various actors, sophisticated optimization and simulation methodologies, parallel or distributed computing environments. The resulting systems would be used not only for policy assessment but also for experimentation and training at the university and industry levels.

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