3,132 research outputs found

    A Bi-objective cap-and-trade model for minimising environmental impact in closed-loop supply chains

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    A Closed-Loop Supply Chain (CLSC) is a complex network with unique environmental features and attributes that requires specific managerial policies and strategies. Quantitative models can provide a solid basis for these policies and strategies. This study expands the work of Shoaeinaeini et al. (2021) on Green Supply Chain Management. We propose a bi-objective facility location, demand allocation, and pricing model for CLSC networks. The proposed model considers two conflicting objective functions: maximising profits and minimising emissions. We show consumer environmental awareness can predict the products’ rate of return and determine a more suitable price for new products and the acquisition price for used products. The cap-and-trade policy has been implemented at its fullest potential, allowing the trading of carbon quotas. Therefore, companies may decide to produce less to sell more quotas or vice-versa, effectively picking the most profitable option. The model is solved and tested with the commercial solver BARON. The model effectively shows the trade-off between generating profits and emission reduction. Companies are able to turn a profit while abiding by the government’s intention of reducing emissions. The comparison with a single-objective version of the model highlights that the concurrent optimisation of economic and environmental objectives yields better results. The acquisition price of used products is a value worthy of monitoring. The government should focus on policies to assist the reverse flow of used products

    Profit-driven planning and analysis of a WEEE recycling facility with a multi-period MILP model

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    Electronic waste is one of the fastest-growing waste streams in the world. The challenges associated with the recycling of Waste Electrical and Electronic Equipment (WEEE) represent both threats, as the improper disposal of this waste can harm the environment and human health, and opportunities, as this category of waste contains valuable and rare resources that can be recovered and repurposed, contributing to the circular economy. The EU is leading the way in improving the collection and treatment of WEEE, but this has not been sufficient to meet the targets set in its WEEE directive. Therefore, additional efforts must be made to ensure the costeffective and environmentally sound recycling of WEEE, both in the public and private sectors. In this thesis, we propose a multi-period MILP model for the planning of a WEEE recycling facility in Belgium and conduct various analyses to provide insights on what elements are the most crucial to the profitability of such a facility. The originality of our approach lies in the multi-period aspect of the model, and the addition of a limited amount of labour to be allocated to various labour-intensive tasks of WEEE recycling. Our main findings are that labour is the most critical resource, both in cost and utilization, such that the optimal quantity of WEEE to process is the one that results in complete utilization of labour, with little to no overtime. As such, the flexibility of labour, both in possible task allocation and overtime capabilities, is crucial to the proper functioning of the facility, especially when taking into account possible deviations from the optimal plan, caused by the heterogeneity of WEEE and other variations such as the timing of deliveries.nhhma

    Dynamic and causality interrelationships from municipal solid waste recycling to economic growth, carbon emissions and energy efficiency using a novel bootstrapping autoregressive distributed lag

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    This study contributes to estimate the municipal solid waste (MSW) recycling effect on environmental quality and economic growth in the United States. Few studies have been given to macro-level aggregate analysis through national scale MSW recycling, environmental, and economic indicators. This study employs bootstrapping autoregressive distributed lag modeling for investigating the cointegration relationship among MSW recycling, economic growth, carbon emissions, and energy efficiency utilized quarterly data from 1990 to 2017. The result implies that a one percent increase in MSW recycling contributes to economic growth and reduce carbon emissions by 0.317% (0.157%) and 0.209% (0.087%) in the long-run (short-run). Similarly, a one percent improvement in energy efficiency stimulates economic growth by 0.489% (0.281%) and mitigates carbon emissions by 0.285% (0.197%) in the long-run (short-run). A higher per capita income and population growth caused higher emissions by 0.197% and 0.401% in the long-run. The overall results reveal stronger impacts in the long-run than the short-run with significant convergence towards long-run equilibrium, suggesting a prominent long-run transmission of economic and environmental fallouts. This study confirms a uni-directional causality from MSW recycling to economic growth, carbon emissions, and energy efficiency. These outcomes signify that any policy intervention related to MSW recycling produces significant changes in the level of economic growth and carbon emissions. The finding provides valuable insight for policymakers to counteract carbon emissions through recyclable waste management that simultaneously create significant economic value

    Sustainable Industrial Engineering along Product-Service Life Cycle/Supply Chain

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    Sustainable industrial engineering addresses the sustainability issue from economic, environmental, and social points of view. Its application fields are the whole value chain and lifecycle of products/services, from the development to the end-of-life stages. This book aims to address many of the challenges faced by industrial organizations and supply chains to become more sustainable through reinventing their processes and practices, by continuously incorporating sustainability guidelines and practices in their decisions, such as circular economy, collaboration with suppliers and customers, using information technologies and systems, tracking their products’ life-cycle, using optimization methods to reduce resource use, and to apply new management paradigms to help mitigate many of the wastes that exist across organizations and supply chains. This book will be of interest to the fast-growing body of academics studying and researching sustainability, as well as to industry managers involved in sustainability management

    Open-Source TIG-Based Metal 3D-Printing

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    Metal 3-D printing has been relegated to high-cost proprietary high-resolution systems and low-resolution low-cost metal inert gas (MIG) systems. In order to provide a path to high-resolution, low-cost, metal 3-D printing, this manuscript proposes a new open source metal 3-D printer design based around a low-cost tungsten inert gas (TIG) welder coupled to a commercial open source self replicating rapid prototyper. Optimal printing parameters for the machine are acquired using a novel computational intelligence software. TIG has many advantages over MIG, such as having a low heat input, clean beads, and the potential for both high-resolution prints as well as insitu alloying of complex geometries. The design can be adapted to most RepRap-class systems and has a basic yet powerful free and open source software (FOSS) package for the characterization of the 3-D printer. This system can be used for fabricating custom metal scientific components and tools, near net-shape structural metal component rapid prototyping, adapting and depositing on existing metal structures, and is deployable for in-field prototyping for appropriate technology applications

    Carbon emission policies impact in logistics supply chain networks

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    Environmental issue is becoming a serious global concern. Human activities associate with industrial activities and households produce a great amount of greenhouse gases, particularly carbon dioxide, and gives significant impact on the environment. The legislation on carbon emissions has become an important agenda in order to control the amount of carbon emissions that might affect the world for future generations. In conjunction to this issue, therefore, the research was conducted to investigate the impact of the carbon emission policies on reverse and forward logistics strategies and operations and propose optimisation models for the paper recycling and fresh produce industry with cases in the UK. The optimal network design approach for both cases under carbon emission control is formulated. The research concluded that exporting the waste paper to Asia is a better option when pollution from the recycling is not charged. However, when considering the carbon emission in both the UK and the Asian country, the best strategy would depend on the amount of recycling and the differences between the costs of the recycling locally and overseas. For fresh produce case, with no carbon policies, road is a better transportation option. However, if the industry has to pay for carbon emission, consideration of multimodal transportation has to be made in order to remain optimal. The analysis of business strategies and configuration of reverse and forward logistics networks are carried out with quantitative optimisation modelling. The analysis for paper recycling and the fresh produce industry consider contributions to the environment and costs in relation to carbon emission. Mixed integer linear programming models were developed for both cases to obtain the optimal choice in strategic and operational decision making. Transportation industry is a main contributor of greenhouse gases that give direct impact to the environment. Multimodal transportation planning is important because it can help to reduce impact on the environment, by using a combination of at least two modes of transportation in a single transport chain, without a change of container for the goods, with most of the route travelled by road, rail, inland waterway or ocean-going vessel and with the shortest possible initial and final journeys by road. Multimodal transportation planning is proposed in the fresh produce industry with another variable which is time. The analytical result derived from sensitivity analysis is discussed to draw academic and practical findings for carbon control policy making and logistics network configuration. The research outcome has a good generic contribution to eco-logistics management of other recycling materials and to generic logistics network configuration issues. The research is also significantly contributed to government policy making in carbon emission control

    A three-phase heuristic approach for reverse logistics network design incorporating carbon footprint

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    Reverse logistics (RL) is emerging as a significant area of activity for business and industry, motivated by both commercial profitability and wider environmental sustainability factors. However, planning and implementing an appropriate RL network within existing supply chains for product recovery that increases customer satisfaction, decreases overall costs, and provides a competitive advantage over other companies is complex. In the current study, we developed a mixed integer linear programming (MILP) model for a reverse logistics network design (RLND) in a multi-period setting. The RL network consists of collection centres, capacitated inspection and remanufacturing centres and customer zones to serve. Moreover, the model incorporates significant characteristics such as vehicle type selection and carbon emissions (through transportation and operations). Since the network design problems are NP-hard, we first propose a solution approach based on Benders decomposition (BD). Then, based on the structure of the problem we propose a three-phase heuristic approach. Finally, to establish the performance and robustness of the proposed solution approach, the results are compared with benchmark results obtained using CPLEX in terms of both solution quality and computational time. From the computational results, we validated that the three-phase heuristic approach performs superior to the BD and Branch &Cut approach

    OPTIMAL INBOUND/OUTBOUND PRICING MODEL FOR REMANUFACTURING IN A CLOSED-LOOP SUPPLY CHAIN

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    The paper presents a model for optimizing inbound and outbound pricing for closed-loop supply chains that remanufacture reusable products. Remanufacturers create reusable products from returned used products and sell the products “as new” to manufacturers or consumers. By implementing a return subsidy, remanufacturers can encourage the consumer to return used products. Demand for the as-new components often depends on the selling price and inventory. The available inventory increases as the subsidy increases and as the price decreases. Our model can determine the optimal subsidy and selling price for used and remanufactured products, respectively. Our model uses the Karush–Kuhn–Tucker conditions to solve its nonlinear problem. Sensitivity analysis reveals how different parameters affect profit under model-optimized conditions

    A bi-objective optimization model for a carbon cap jit distribution network

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    The environmental protection concerns and legislation are pushing companies to redesign and plan their activities in an environmental friendly manner. This will probably be done by constraining companies to emit less than a given amount of carbon dioxide per product that is being produced and transported. In addition, some companies may volunteer to reduce their carbon footprint. Consequently, companies will face new constraints that force them to reduce carbon emissions while still minimizing production and transportation costs. Transportation is at the heart of logistics activities and is one of the leading sources of greenhouse gas emissions. The emitted carbon dioxide through transportation activities is accounting for almost 80% of the total greenhouse gas emissions. The need to implement Just-In-Time (JIT) strategy for transporting small batch sizes seems to beagainst environmental concerns. The JIT principles favor small and frequent deliveries by many small rush transports with multiple regional warehouses. Although several attempts have been made to analyze green supply chain networks, little attention has been paid to develop JIT distribution models in carbon constrained environment. Incorporation of environmental objectives and constraints with JIT distribution will generate new problems resulting in new combinatorial optimization models. In addition, these objectives and constraints will add to the model complexities. Both areas require to be investigated. In this research, a bi-objective carbon-capped logistic model was developed for a JIT distribution that takes into account different carbon emission constraints. The objectives include minimization of total costs and carbon cap. Since the studied problem is Non-deterministic Polynomial-time Hard (NP-Hard), a nondominated sorting genetic algorithm-II (NSGA-II) was employed to solve the problem. For validation and verification of the obtained results, non-dominated ranking genetic algorithm (NRGA) was applied. Then, Taguchi approach was employed to tune the parameters of both algorithms; their performances were then compared in terms of some multi-objective performance measures. For further improvements of NSGA-II, a modified firefly algorithm as local searcher was applied. Seven problems with different sizes of small, medium, and large were designed in order to simulate the different cases. The findings have significant implications for the understanding of how varying carbon cap could significantly affect total logistics costs and total carbon emission. More specifically, the results also demonstrated devising policies that enable companies to decide when and how to fulfill the required carbon cap could let firms fulfill these caps at significantly lower costs with lower carbon emission. In addition to these findings, the performance of the proposed solution methodology demonstrated higher efficiency particularly in terms of less CPU time usage by 6.62% and higher quality of obtained solutions by 5.14% on average for different sizes of the problem as compared to the classical NSGA-II
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