674 research outputs found

    Integrating operations research into green logistics:A review

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    Logistical activities have a significant global environmental impact, necessitating the adoption of green logistics practices to mitigate environmental effects. The COVID-19 pandemic has further emphasized the urgency to address the environmental crisis. Operations research provides a means to balance environmental concerns and costs, thereby enhancing the management of logistical activities. This paper presents a comprehensive review of studies integrating operations research into green logistics. A systematic search was conducted in the Web of Science Core Collection database, covering papers published until June 3, 2023. Six keywords (green logistics OR sustainable logistics OR cleaner logistics OR green transportation OR sustainable transportation OR cleaner transportation) were used to identify relevant papers. The reviewed studies were categorized into five main research directions: Green waste logistics, the impact of costs on green logistics, the green routing problem, green transport network design, and emerging challenges in green logistics. The review concludes by outlining suggestions for further research that combines green logistics and operations research, with particular emphasis on investigating the long-term effects of the pandemic on this field.</p

    Operations Research for Green Logistics – An Overview of Aspects, Issues, Contributions and Challenges

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    The worldwide economic growth of the last century has given rise to a vast consumption of goods while globalization has led to large streams of goods all over the world. The production, transportation, storage and consumption of all these goods, however, have created large environmental problems. Today, global warming, created by large scale emissions of greenhouse gasses, is a top environmental concern. Governments, action groups and companies are asking for measures to counter this threat. Operations research has a long tradition in improving operations and especially in reducing costs. In this paper, we present a review that highlights the contribution of operations research to green logistics, which involves the integration of environmental aspects in logistics. We give a sketch of the present and possible developments, focussing on design, planning and control in a supply chain for transportation, inventory of products and facility decisions. While doing this, we also indicate several areas where environmental aspects could be included in OR models for logistics

    Reefer logistics and cool chain transport

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    Reefer logistics is an important part of the cool chain in which reefer containers are involved as the packaging for transporting perishable goods. Reefer logistics is challenging, as it deals with cost and time constraints as well as the product quality and sustainability requirements. In many situations, there is a trade-off between these factors (e.g., between transportation time and the quality of fresh products). Furthermore, considering the high value of reefers, the efficient logistics of is as important as the efficient cargo flows. This causes technical complications and the conflict of interests between actors, especially, between cargo owners (or shippers) and the asset owners (or transport/terminal operators). Improving the efficiency of reefer logistics calls for a thorough understanding of the trade-offs and complexities. This paper aims to help develop such an understanding using a systematic literature review and a socio-technical system analysis. The results can be used to provide managerial insights for actors involved in a cool chain to design tailored solutions for reefer

    Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

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    Railway systems are time-varying and complex systems with nonlinear behaviors that require effective optimization techniques to achieve optimal performance. Evolutionary algorithms methods have emerged as a popular optimization technique in recent years due to their ability to handle complex, multi-objective issues of such systems. In this context, genetic algorithm (GA) as one of the powerful optimization techniques has been extensively used in the railway sector, and applied to various problems such as scheduling, routing, forecasting, design, maintenance, and allocation. This paper presents a review of the applications of GAs and their variants in the railway domain together with bibliometric analysis. The paper covers highly cited and recent studies that have employed GAs in the railway sector and discuss the challenges and opportunities of using GAs in railway optimization problems. Meanwhile, the most popular hybrid GAs as the combination of GA and other evolutionary algorithms methods such as particle swarm optimization (PSO), ant colony optimization (ACO), neural network (NN), fuzzy-logic control, etc with their dedicated application in the railway domain are discussed too. More than 250 publications are listed and classified to provide a comprehensive analysis and road map for experts and researchers in the field helping them to identify research gaps and opportunities

    Green logistic network design : intermodal transportation planning and vehicle routing problems.

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    Due to earth\u27s climate change and global warming, environmental consideration in the design of logistic systems is accelerating in recent years. In this research we aim to design an efficient and environmentally friendly logistical system to satisfy both government and carriers. In particular, we considered three problems in this dissertation: intermodal network design, deterministic green vehicle routing problem and stochastic green vehicle routing problem. The first problem aims to design an economic and efficient intermodal network including three transportation modes: railway, highway and inland waterway. The intent of this problem is to increase the utilization percentage of waterway system in the intermodal transportation network without increasing the cost to the consumer. In particular, we develop a real world coal transportation intermodal network across 15 states in the United States including highway, railway and inland waterway. The demand data were obtained from the Bureau of Transportation Statistics (BTS) under the US Department of Transportation (DOT). Four boundary models are built to evaluate the potential improvement of the network. The first boundary model is a typical minimum cost problem, where the total transportation cost is minimized while the flow balance and capacity restrictions are satisfied. An additional constraint that help obtain an upper bound on carbon emission is added in the second boundary model. Boundary model 3 minimizes the total emission with flow balance and capacity restrictions the same as boundary model 1. Boundary model 4 minimizes the total emission with an additional current cost restriction to achieve a less-aggressive lower bound for carbon emission. With a motivation to minimize the transportation and environmental costs simultaneously, we propose multi-objective optimization models to analyze intermodal transportation with economic, time performance and environmental considerations. Using data from fifteen selected states, the model determines the tonnage of coal to be transported on roadways, railways and waterways across these states. A time penalty parameter is introduced so that a penalty is incurred for not using the fastest transportation mode. Our analysis provides authorities with a potential carbon emission tax policy while minimizing the total transportation cost. In addition, sensitivity analysis allows authorities to vary waterway, railway and highway capacities, respectively, and study their impact on the total transportation cost. Furthermore, the sensitivity analysis demonstrates that an intermodal transportation policy that uses all the three modes can reduce the total transportation cost when compared to one that uses just two modes. In contrast with traditional vehicle routing problems, the second problem intends to find the most energy efficient vehicle route with minimum pollution by optimization of travel speed. A mixed integer nonlinear programming model is introduced and a heuristic algorithm based on a savings heuristic and Tabu Search is developed to solve the large case for this problem. Numerical experiments are conducted through comparison with a solution obtained by BONMIN in GAMS on randomly generated small problem instances to evaluate the performance of the proposed heuristic algorithm. To illustrate the impact of a time window constraint, travel speed and travel speed limit on total carbon emission, sensitivity analysis is conducted based on several scenarios. In the end, real world instances are examined to further investigate the impact of these parameters. Based on the analysis from the second problem, travel speed is an important decision factor in green vehicle routing problems to minimize the fuel cost. However, the actual speed limit on a road may have variance due to congestion. To further investigate the impact of congestion on carbon emission in the real world, we proposed a stochastic green vehicle routing problem as our third problem. We consider a green vehicle problem with stochastic speed limits, which aims to find the robust route with the minimum expected fuel cost. A two-stage heuristic with sample average approximation is developed to obtain the solution of the stochastic model. Computational study compares the solutions of robust and traditional mean-value green vehicle routing problems with various settings

    Towards Sustainable Freight Energy Management - Development of a Strategic Decision Support Tool

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    Freight transportation, in its current shape and form, is on a highly unsustainable trajectory. Global demand for freight is ever increasing, while this demand is predominantly serviced by inefficient, fossil fuel dependent transportation options. The management of energy use in freight transportation has been identified as a significant opportunity to improve the sustainability of the freight sector. Given the vast amount of energy mitigation measures and policies to choose from to attempt this, decision-makers need support and guidance in terms of selecting which policies to adopt – they are faced with a complex and demanding problem. These complexities result, in part, from the vast range, scope and extent of measures to be considered by decision-makers. The tool developed needs to encompass a suitable methodology for comparing proverbial apples to oranges in a fair and unbiased manner, despite the development of one consistent assessment metric that can accommodate this level of diversity being problematic. Further to this, decision-makers need insight into the extent of implementation that is required for each measure. Because the level of implementation of each measure is variable and the extent to which each adopted measure will be implemented in the network needs to be specified, the number of potential measure implementation combinations that decision-makers need to consider is infinite, adding further complexity to the problem. Freight energy management measures cannot, and should not, be evaluated in isolation. The knock-on effects of measure adoption on the performance of other measures need to be considered. Measures are not all independent and decision-makers need to take these dependencies and their ramifications into account. In addition, there is dimensionality to be accounted for in terms of each measure, because one measure can be applied in a variable manner across different components of the freight network. A unique and independent decision needs to be made on the application of a measure for each of these network components (for example for each mode). Decisions on freight transportation impact all three traditional pillars of sustainability: social, environmental and economic. Measure impacts, thus, need to be assessed over multiple criteria. Decisions will affect a variety of stakeholders and outcomes must be acceptable to a range of interested parties. Sustainability criteria are often in conflict with one another, implying that there are trade-offs to be negotiated by the decision-makers. Decision-makers, thus, need to propose system alterations, or a portfolio of system alterations, that achieve improvements in some sustainability respects, whilst maintaining a balance between all other sustainability aspects. Moreover, the magnitude of impacts (be it positive or negative) of a measure on the sustainability criteria is variable, adding additional dimensionality to the problem. The aim of the research presented in this dissertation was to develop a decision support tool which addresses the complexities involved in the formulation of freight transport energy management strategies on behalf of the decision-makers, facilitating the development of holistic, sustainable and comprehensive freight management policy by government level decision-makers. The Freight Transport Energy Management Tool (FTEMT) was developed in response to this research objective, using a standardised operations research approach as a roadmap for its development. Following a standardised operations research approach to model development provides a structure where stakeholder participation can be encouraged at all the key stages in the decision-making process; it offers a logical basis for proposing solutions and for assessing any proposed suggestions by others; it ensures that the appraisal of alternative solutions is conducted in a logical, consistent and comprehensive manner against the full set of objectives; and it provides a means for assessing whether the implemented instruments have performed as predicted, enabling the improvement of the model being developed. The FTEMT can be classified as a simulation optimisation model, which is a combination between multi-objective optimisation and simulation. The simulation component provides a suitably accurate representation of the freight system and affords the ability to approximate the effect that measure implementation will have on the sustainability objectives, whilst the optimisation component provides the ability to effectively explore the decision space and reduces the number of alternative options (and, therefore, the complexity) that decision-makers need to consider. It is this simulation optimisation backbone of the FTEMT that enables the tool to address all the complexities surrounding the problem, enabling the decision support produced by the FTEMT to provide the information necessary for decision-makers to steer the freight transport sector towards true sustainability. Although this problem originates from the domain of sustainable transportation planning, the combination of operations research and transport modelling knowledge applied proved essential in developing a decision support tool that is able to generate adequate decision support on the problem. To demonstrate the use and usefulness of the decision support system developed, a fictitious case study version of the FTEMT was modelled and is discussed throughout this dissertation. Results from the case study implementation were used to verify and validate the tool, to demonstrate the decision support generated and to illustrate how this decision support can be interpreted and incorporated into a decision-making process. Outputs from the case study FTEMT proved the tool to be operationally valid, as it successfully achieved its stated objectives (the FTEMT unearths a Pareto set of solutions close to the true efficient frontier through the exploration of different energy management measure combinations). Explained in short, the value of using the FTEMT to generate decision support is that it explores the decision space and reduces the number of decision alternatives that decision-makers need to consider to a manageable number of solutions, all of which represent harmonic measure combinations geared toward optimal performance in terms of the entire spectrum of the problem objectives. These solutions are developed taking all the complexity issues surrounding the problem into account. Decision-makers can, thus, have confidence that the acceptance of any one of the solutions proposed by the FTEMT will be a responsible and sound decision. As an additional benefit, preferences and strategic priorities of the decision-makers can be factored in when selecting a preferred decision alternative for implementation. Decision-makers must debate the trade-offs between solutions and need to determine what they are willing to sacrifice to realise what gain, but they are afforded the opportunity to select solutions that show the greatest alignment with their official mandates. The structure of the FTEMT developed and described in this dissertation presents a practical methodology for producing decision support on the development of sound freight energy management policy. This work serves as a basis to stimulate further scholarship and expands upon the collective knowledge on the topic, by proposing an approach that is able to address the full scale of complexities involved in the production of such decision support

    The Selection of Intermodal Transport System Scenarios in the Function of Southeastern Europe Regional Development

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    The development of intermodal transportation (IT) systems is of vital importance for the sustainability of logistics activities. The existing research point at individual directions of action for system improvement and increase of IT participation in overall transportation, thus reducing negative impacts of logistics on sustainability. However, there is a lack of research defining complex scenarios that unite existing ideas and concepts of IT system development and improvement. Accordingly, this article deals with the definition and selection of the most appropriate IT development scenario for the region of Southeastern Europe. Six different potential scenarios that differ in the network configuration, the required level of logistics infrastructure development, the role of different IT terminal categories, the involvement of different transportation modes, and goods flows’ transformation degree, are defined. The scenarios are analyzed according to four stakeholder groups and twelve defined criteria. A novel hybrid multi-criteria decision-making model, based on fuzzy Delphi, fuzzy Factor Relationship (FARE), and fuzzy Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods, is developed for solving the problem. The definition and analysis of the problem, the way of establishing the scenarios, as well as the development of a novel hybrid model are the main contributions of this article. A significant contribution is also the consideration of the Dry Port (DP) concept for the first time in the context of river ports. The results indicate that the scenario referring to the development of the IT core network with the Danube DP terminals is potentially the most appropriate scenario for the Southeastern Europe IT system

    Sea Container Terminals

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    Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

    Mixing quantitative and qualitative methods for sustainable transportation in Smart Cities

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