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

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

A Review on Remanufacturing Reverse Logistics Network Design and Model Optimization

Remanufacturing has gained great recognition in recent years due to its economic and environmental benefits and effectiveness in the value retention of waste products. Many studies on reverse logistics have considered remanufacturing as a key node for network optimization, but few literature reviews have explicitly mentioned remanufacturing as a main feature in their analysis. The aim of this review is to bridge this gap. In total, 125 papers on remanufacturing reverse logistics network design have been reviewed and conclusions have been drawn from four aspects: (1) in terms of network structure, the functional nodes of new hybrid facilities and the network structure combined with the remanufacturing technologies of products are the key points in the research. (2) In the mathematical model, the multi-objective function considered from different aspects, the uncertainty of recovery time and recovery channel in addition to quantity and quality, and the selection of appropriate algorithms are worth studying. (3) While considering product types, the research of a reverse logistics network of some products is urgently needed but inadequate, such as medical and furniture products. (4) As for cutting-edge technologies, the application of new technologies, such as intelligent remanufacturing technology and big data, will have a huge impact on the remanufacturing of a reverse logistics network and needs to be considered in our research

SC-TVP Green Practice Initiative in China’s Logistics Market Based on Case Analysis

In the era of circular economy, the concept of sustainable development has attracted more and more attention. With the development of cross-border e-commerce, the demand for logistics services has continued to surge, and the pressure on them to provide sustainable services has risen sharply. In 2020, China officially put forward the “double carbon” strategic goal, and green logistics has become the new direction of industry development, in line with the concept of sustainable development. However, the actual impact of green logistics practice on China’s sustainable logistics services is unknown. This paper aims to study the current situation and results of green logistics practice through data analysis and case analysis, including green design, green transportation, green management and other indicators. Based on the case analysis in this paper, the SC-TVP model is constructed to provide an effective green logistics practice framework, with a view to improving the management level of green logistics, promoting the development of enterprises, and providing some reference for the logistics development in the post-epidemic era

End-of-life vehicle management: a comprehensive review

Waste management is gaining very high importance in recent years. As automotive is one of the most critical sectors worldwide, which is rapidly increasing, the management of end-of-life vehicles (ELVs) gains importance day by day. Due to legislation and new regulations, actors like users, producers, and treatment facilities are being conferred new responsibilities in the ELV management process. Besides, the ELV management is of vital importance for environment conservation, circular economy and sustainable development. All of these reasons are making the ELV management such a crucial issue to study. Today, the ELV management is a well-positioned and emergent research area. However, the available review papers are focused only on a small area of the ELV management, such as reverse logistics, recovery infrastructure, disassemblability, etc. Besides, a review of state-of-the-art mathematical models for the ELV management is still missing. This paper aims to provide an extensive content analysis overview of studies on the ELV management. A total of 232 studies published in the period 2000-2019 are collected, categorized, reviewed and analyzed. A critical review of the published literature is provided. Gaps in the literature are identified to clarify and suggest future research directions. This review can provide a source of references, valuable insights, and opportunities for researchers interested in the ELV management and inspire their additional attention

Green Logistics development and evaluation of the carbon footprint

Along with the worldwide climate changing, human activities and the rapid deterioration of the environment, Low-carbon economy in recent years become increasingly focus of attention in people's lives. The economic reform will gradually penetrate into the logistics system, modern logistics as a composite service industry, play a decisive role in the modern division of labor and cooperation under the social environment, it is a manufacturing! The important supporting business is an important bridge between production and consumption. The logistics industry is in a period of rapid development, the logistics process not only energy consumption demand is big, and the C02 emissions are also large. Coupled with the destruction of the human living environment, the greenhouse effect becomes more and more prominent, more the need of the development of green logistics, low carbon logistics. However, at home and abroad for most of the research of this aspect is still stay in the stage of qualitative analysis, quantitative analysis of the literature on energy consumption and C02 emission of less amount of logistics system. There are four objectives will be discussed. The first objective is the relevant literature on the green logistics is summarized, which lays the foundation for the research in this paper, green logistics. The second objective is the energy consumption and C02 calculation models were summarized, to provide reference for other scholars to conduct relevant research. The third objective is through statistical analysis, master the different modes of transport energy consumption and C02 emissions, and provide the basis for enterprises to choose the mode of transport. The fourth objective combining with specific examples, analyzed the carbon footprint of the logistics process instance modeling based on LCA.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Solving of Location-Allocation-Routing Model of Reverse Supply Chain for End-of-Life Vehicles Considering Sustainability Dimensions Under Uncertainty Conditions

Abstract In recent years, the concept of reverse logistics has been paid attention by many researchers due to the importance of environmental laws as well as the importance of utilizing from worn-out goods for re-production. In the process of reverse logistics, a systematic manufacturer accepts items such as recycling, reproduction and land filling for products that reach the endpoint of consumption. It is very necessary to address the issue of reverse logistics network and its effective management and guidance. According to the studies, taking into account the uncertainty conditions is one of the most effective factors of modeling reverse logistics network. In reverse logistics, parameters such as capacity of centers, demand, cost and quality are uncertain. With considering the above mentioned issues, the purpose of present study was to develop a mixed fuzzy integer linear planning model for reverse logistics network of EOL vehicles in order to minimize the cost of establishing and constructing facilities, as well as minimizing transportation and material costs between facilities, minimizing environmental impacts, and maximizing social responsibility with taking into account the uncertainty conditions and the multi-product mode. Due to the NP-HARD nature of understudy problem, the Whale optimization algorithm (WOA) and NSGA-II algorithm were used to solve the model, which results of these two modes were comprised based on quality indicators, dispersion and uniformity and solution time of problem

Design and control of carbon aware supply chains

In this dissertation the impact of carbon emissions on the design and control of supply chains is studied. Increasing awareness for global warming and the role of greenhouse gasses in this has made companies more aware of carbon dioxide emissions caused by supply chains. As a result of this awareness, carbon emission regulations have been developed enforcing companies to incorporate a carbon cost (for certain activities in certain regions). Moreover, companies are voluntarily restricting their carbon emissions by specifying emission reduction targets, as a response to pressure from customers and stakeholders. In this dissertation we develop models with emission regulation and also with voluntary emission targets. We study well-known trade-offs in the field of operations management, such as between inventory and transport costs, by incorporating a carbon emission component, historically often neglected, and investigate the impact of the emissions on decisions. It is important for companies to take carbon emissions explicitly into account in decision making as carbon related costs are expected to increase in the future. Carbon emissions can be reduced to a certain extent by taking efficiency measures that both reduce emissions and costs. As companies can also invest in these measures from a pure cost perspective, we do not consider them in this dissertation. Moreover, it is likely that these measures yield insufficient emission reductions to achieve global emission targets. Hence, to achieve substantial emission reductions, measures that require investments, or increase operational costs, might be necessary. We explore several strategies for companies to reduce carbon emissions and investigate when a certain strategy is cost-effective. Examples of emission reduction strategies are to switch transportation to a mode with lower emissions, or to invest in production technology or off-shore production capacity. The focus of the research is on production companies and their carbon emissions generated during production and transportation activities, either to facilities of the same company or from suppliers or to customers. When considering emissions from transportation, we assume that transport is executed by a third party logistics service provider, as is often seen in practice. As a result, the control of the production company over the transport (emissions) is limited. The optimization of the load of the vehicle, and the traveled route is outside the control of the production company. However, the production company can decide which transport mode, or combination of modes be used, which determines the emissions to a large extent. In Chapters 2, 3, and 4, this emission reduction opportunity is studied in settings with one or multiple products and imposing the use of one or two modes. Then, in Chapter 5, the focus is extended to include emissions from production. We consider a company facing emission regulation for production and consider the possibility to invest in cleaner technology or to offshore production to a location without emission regulation. We next present a summary of the models and results presented in Chapters 2 through 5. First, in Chapter 2, we study the transport mode selection decision for a single product subject to emission regulation. We investigate the impact of different types of emission regulations and investigate under what circumstances a transport mode switch may occur. A transport switch implies that the selected transport mode in a setting with emission regulation differs from the selected mode in absence of emission regulation. The tradeoff under consideration is that a fast mode results in low inventory costs but in high transportation costs and emissions (costs), and vice versa. In a setting with stochastic demand we consider an order-up-to inventory policy including an emission cost. To accurately estimate the carbon emissions from transportation, we use a carbon emission measurement methodology based on real-life data and incorporate it into an inventory model. We observe that not the emission cost but the product characteristics, such as weight, density, and value, mainly determine which transport mode is selected. Consequently, a switch to a less polluting transport mode only results for a very high emission cost or if a product has a low weight or density or a high value. We find that even though large emission reductions can be obtained by switching to a different mode, the actual decision depends on the regulation and non-monetary considerations, such as lead time variability. Then, in Chapter 3, we consider a multi-item setting in which a self-imposed emission reduction target is set for a group of items. One item represents a combination of a particular product and a particular customer for which regular shipments occur, which determines the demand, product characteristics and the distance to be traveled. As the choice of transport mode (and corresponding transport costs) is up to the production company, the quoted price to the customer is also a decision variable. Since a single emission constraint is set for a group of items, the model is a constrained multi-item deterministic problem which can be solved using Lagrangian relaxation. Setting an emission target for a group of items allows for taking advantage of the portfolio effect: reducing emissions first where it is overall less costly. For a fixed emission target the transport mode that minimizes the total logistics cost is selected. If a range of emission targets are considered and we compare the cost-minimizing solutions, then it appears that two opportunities exist for the producer to reduce emissions: first of all, to select a mode that results in lower emissions per product shipped, and secondly to select a slightly higher sales price which results in lower demand and hence lower emissions. In a case study, we apply our model (with fixed sales price) to a business unit of Cargill and observe that emissions can be reduced by 10% at virtually no cost increase. Emissions can be reduced by at most 27% which results in a 30% cost increase. In an extension in which the sales price can be set, we observe that the portfolio effect results in at most 20% profit savings, a value which is relatively robust to price-sensitivity of demand. As in this case study road transport is the most polluting mode, larger emission reductions can be expected when air transport is used for shipments. Next, in Chapter 4 we examine the possibility to use two supply modes for a given product simultaneously, which is referred to as dual sourcing in inventory literature, in a multi-item emission-constrained setting with stochastic demand. By using two supply modes, a fast and a slow, one can combine the low transport costs and emissions (the slow mode) with being highly responsive (the fast mode) when required, i.e. in case of a stock out situation. As has been investigated in the literature using dual sourcing may result in lower expected period costs than using only a single mode. From an emission perspective using dual sourcing is beneficial compared to single sourcing since emission reductions can be achieved on a continuous scale. In some situations switching all shipments to a less polluting mode is too costly. Dual sourcing may then provide a large part of the emission reduction at a lower cost than using only the slow mode. We assume that a so-called single-index policy is used, which specifies two order-up-to levels: one for each mode. As a result of this policy, the fast mode is used when the demand in a certain period exceeds a certain value. Making use of a special case with exponentially distributed demand, we provide structural insights for a single product model. Then we extend these results to a model with two products and an aggregate emission constraint which provides insight into the more general situation with n products. In a numerical study we observe that if dual sourcing results in a cost decrease, then emissions can be reduced to a large extent without increasing the costs compared to using only a single mode. For a two-product setting we study if setting an emission constraint for a group of items is more or less beneficial if the products are more similar with respect to the value for one variable. We observe that the demand variability, and not so much for product weight and the penalty cost factor, has a large impact on how beneficial dual sourcing is, i.e. less similar products benefit less from dual sourcing. Lastly, we study the investments of a production company in production technology and capacity under asymmetric and uncertain emission regulation in Chapter 5. Asymmetric emission regulation refers to the fact that in different regions of the world different, or no, emission regulations exist and as result the emission price differs from region to region. We consider a producer of an energy-intensive good which incurs an emission cost for emissions generated during production. The company is deciding how much to invest in production technology in the regulated market, and how much capacity to build in a location with no emission regulation, the unregulated market. As emission regulation may result in off-shoring production and an increase in total emissions, regulators can implement measures to combat this undesirable effect. We refer to these measures as anti-leakage policies and study for each policy how it affects the company’s investment decisions and ultimately global emissions. We consider three different anti-leakage policies: Border Tax, which imposes a cost for products imported into the regulated region, Output-based allocation, which reimburses a certain emission cost per product produced in the regulated market, and Grandfathering, which reimburses a lump sum of emission cost, provided actual emissions exceed the amount. We consider four scenarios, one without an anti-leakage policy (baseline scenario) and three for the anti-leakage policies just described, and determine the optimal investment strategy and also the production strategy, which specifies how much to produce in each location given an emission cost realization, and the global emissions. We have observed that four possible strategies exist, two of which are to invest and produce only in one market (either the regulated or the unregulated) and two involve investment in both markets. When an anti-leakage policy is implemented and we compare the investments to the baseline scenario two effects may occur. First of all, less capacity may be built in the unregulated market, while not changing the production strategy. Secondly, it may result in the selection of a strategy with more production in the regulated market. We have applied our model to a data set based on a European-based cement producer and conducted a full factorial study for several important parameters. Overall we have observed that the grandfathering policy is preferred from both the company’s and regulator’s perspective. It is however, important to set the reimbursement not too low or too high. Finally, in Chapter 6 we present the conclusions of the research presented in this dissertation and provide directions for future research

Extending the supply chain to address sustainability

© 2019 Elsevier Ltd In today's growing economy, overconsumption and overproduction have accelerated environmental deterioration worldwide. Consumers, through unsustainable consumption patterns, and producers, through production based on traditional resource depleting practices, have contributed significantly to the socio-environmental problems. Consumers and producers are linked by supply chains, and as sustainability became seen as a way to reverse socio-environmental degradation, it has also started to be introduced in research on supply chains. We look at the evolution of research on sustainable supply chains and show that it is still largely focused on the processes and networks that take place between the producer and the consumer, hardly taking into account consumer behavior and its influence on the performance of the producer and the supply chain itself. We conclude that we cannot be talking about sustainability, without extending the supply chains to account for consumers' behavior and their influence on the overall system performance. A conceptual framework is proposed to explain how supply chains can become sustainable and improve their economic and socio-environmental performance by motivating consumer behavior toward green consumption patterns, which, in turn, motivate producers and suppliers to change their operations

Low Carbon Freight Services Analysis: A Review Study

ABSTRACT_ The analysis of Low Carbon Freight Services is relatively recent. However, the topic has become one of the most popular in freight services research literature. A review of 80 Low Carbon Freight Services papers, published in the literature during the period 1995-2015, was undertaken to provide Freight Services researchers with a reference guide to the context, method and focus of previous studies. The outcome of these papers show there is some benefits to employ low carbon freight logistic include Economic benefits, Environmental benefits, Operational benefits and Intangible benefits. The study describes opportunities and contributions in relation to an increase in a competitiveness and flexibility of enterprise and all of participating supply chain segments

Sustainable reverse logistics for household plastic waste

Summary of the thesis titled “Sustainable Reverse Logistics for Household Plastic Waste” PhD Candidate: Xiaoyun Bing Recycled plastic can be used in the manufacturing of plastic products to reduce the use of virgin plastics material. The cost of recycled plastics is usually lower than that of virgin plastics. Therefore, it is environmentally and economically beneficial to improve the plastic recycling system to ensure more plastic waste from households is properly collected and processed for recycling. Plastic waste has a complex composition and is polluted, thus requires a substantial technical effort to separate the plastics from the waste and to sort these into recyclable materials. There are several alternatives in the existing collection methods (curb-side and drop-off) and separation methods (source separation and post-separation). It is challenging to select a suitable combination of these methods and to design a network that is efficient and sustainable. It is necessary to build a suitable, efficient and sustainable recycling network from collection to the final processor in order to provide solutions for different future scenarios of plastics household waste recycling. Decision support is needed in order to redesign the plastic waste reverse logistics so that the plastic waste recycling supply chain can be improved towards a more sustainable direction. To improve the efficiency in the recycling of plastic packaging waste, insights are required into this complex system. Insights solely on a municipal level are not sufficient, as the processing and end market are important for a complete network configuration. Therefore, we have investigated the problem at three levels: municipal, regional, and global. Decision support systems are developed based on optimization techniques to explore the power of mathematical modelling to assist in the decision-making process. This thesis investigates plastic waste recycling from a sustainable reverse logistics angle. The aim is to analyse the collection, separation and treatments systems of plastic waste and to propose redesigns for the recycling system using quantitative decision support models. We started this research project by identifying research opportunities. This was done through a practical approach that aimed to find future research opportunities to solve existing problems (Chapter 2). We started from a review of current municipal solid waste recycling practices in various EU countries and identified the characteristics and key issues of waste recycling from waste management and reverse logistics point of view. This is followed by a literature review regarding the applications of operations research. We conclude that waste recycling is a multi-disciplinary problem and that research opportunities can be found by considering different decision levels simultaneously. While analyzing a reverse supply chain for Municipal Solid Waste (MSW) recycling, a holistic view and considering characteristics of different waste types are necessary. Municipal Level In Chapter 3, we aim to redesign the collection routes of household plastic waste and compare the collection options at the municipal level using eco-efficiency as a performance indicator. The collection problem is modeled as a vehicle routing problem. A tabu search heuristic is used to improve the routes. Scenarios are designed according to the collection alternatives with different assumptions in collection method, vehicle type, collection frequency, and collection points, etc. The results show that the source-separation drop-off collection scenario has the best performance for plastic collection, assuming householders take the waste to the drop-off points in a sustainable manner. In Chapter 4, we develop a comprehensive cost estimation model to further analyze the impacts of various taxation alternatives on the collection cost and environmental impact. This model is based on such variables as fixed and variable costs per vehicle, personnel cost, container or bag costs, as well as emission costs (using imaginary carbon taxes). The model can be used for decision support when strategic changes to the collection scheme of municipalities are considered. The model, which considers the characteristics of municipalities, including degree of urbanization and taxation schemes for household waste management, was applied to the Dutch case of post-consumer plastic packaging waste. The results showed that post-separation collection generally has the lowest costs. Curb-side collection in urban municipalities without residual waste collection taxing schemes has the highest cost. These results were supported by the conducted sensitivity analysis, which showed that higher source-separation responses are negatively related to curb-side collection costs. Regional Level Chapter 5 provides decision support for choosing the most suitable combination of separation methods in the Netherlands. Decision support is provided through an optimized reverse logistics network design that makes the overall recycling system more efficient and sustainable, while taking into account the interests of various stakeholders (municipalities, households, etc.). A mixed integer linear programming (MILP) model, which minimizes both transportation cost and environmental impact, is used to design this network. The research follows the approach of a scenario study; the baseline scenario is the current situation and other scenarios are designed with various strategic alternatives. Comparing these scenarios, the results show that the current network settings of the baseline situation is efficient in terms of logistics, but has the potential to adapt to strategic changes, depending on the assumptions regarding availability of the required processing facilities to treat plastic waste. In some of the tested scenarios, a separate collection channel for polyethylene terephthalate (PET) bottles is cost-efficient and saves carbon emission. Although the figures differ depending on the choices in separation method made by municipalities, our modeling results of all the tested scenarios show a reduction in carbon emissions of more than 25 percent compared to the current network. Chapter 6 studies a plastic recycling system from a reverse logistics angle and investigates the potential benefits of a multimodality strategy to the network design of plastic recycling. The aim was to quantify the impact of multimodality in the network in order to provide decision support for the design of more sustainable plastic recycling networks in the future. A MILP model is developed in order to assess different plastic waste collection, treatment, and transportation scenarios. A baseline scenario represents the optimized current situation, while other scenarios allow multimodality options (barge and train) to be applied. With our input parameter settings, results show that transportation costs contribute to approximately 7 percent of the total costs, and multimodality can help reduce transportation costs by almost 20 percent (CO_2-eq emissions included). In our illustrative case with two plastic separation methods, the post-separation channel benefits more from a multimodality strategy than the source-separation channel. This relates to the locations and availability of intermediate facilities and the quantity of waste transported on each route. Global Level After the regional network redesign, Chapter 7 shows a global network redesign. The aim of this chapter was to redesign a reverse supply chain from a global angle based on a case study conducted on household plastic waste distributed from Europe to China. Emissions trading restrictions are set on processing plants in both Europe and China. We used a mixed-integer programming model in the network optimization to decide on location reallocation of intermediate processing plants under such restrictions, with the objective of maximizing total profit under Emission Trading Schemes (ETS). Re-locating facilities globally can help reduce the total cost. Once carefully set, ETS can function well as incentive to control emissions in re-processors. Optimization results show that relocating re-processing centers to China reduces total costs and total transportation emissions. ETS applied to re-processors further helps to reduce emissions from both re-processors and the transportation sector. Carbon caps should be set carefully in order to be effective. These results give an insight in the feasibility of building a global reverse supply chain for household plastic waste recycling and demonstrate the impact of ETS on network design. The results also provide decision support for increasing the synergy between the policy for global shipping of waste material and the demand of recycled material. Conclusions Chapter 8 summarizes the findings from chapters 2 to 7 and provides brief answers to the research questions. Beyond that, the integrated findings combine the results from different decision levels and elaborate the impacts of various system characteristics and external factors on the decision making in order to achieve an improved sustainable performance. Main findings are: Regarding the impact of carbon cost, the results from different chapters are consistent in terms that emission cost is only a small part of the total cost, even when carbon cost is set at its historically highest figure. When carbon price is set to a different value, impact of carbon cost on the change of optimization results is higher on the upstream of the reverse supply chain for plastic waste than the downstream.In Emission Trading scheme (ETS), carbon cap has a larger impact on eco-efficiency performance of the global network than carbon price.On one decision level, models can help to find the ``best option". For example, in the collection phase, the average total collection costs per ton of plastic waste collected for source-separation municipalities are more than twice of the post-separation municipalities' collection costs due to the frequent stops made and idling time at each stop. From the regional network perspective, post-separation scenarios have higher costs and environmental impact than source separation due to the limited number of separation centers compared to the numerous cross-docking sites for source-separation. When combining decision levels, however, it is difficult to find one ``best option" that fits all, as there are contradictory results when looking at the same factor from different decision levels. Through decision support models, we provided clear insights into the trade-offs and helped to quantify the differences and identify key factors to determine the differences.Population density differences in various municipalities influence the performance of curbside collection more than drop-off collection. This information is valuable for decision makers to consider in the decision making process. Finally, managerial insights derived from sustainable reverse logistics for household plastic waste are summarized in conclusion section.</p