A hybrid model for remanufacturing facility location problem in a closed-loop supply chain

Traditional supply chain design is merely based on the open loop or forward flow of materials, neglecting reverse flow for recovery of materials despite the recent concerns of customers and governments about environmental and production cost reductions. New supply chain design should be closed loop which implements traditional supply chain concepts with reverse flow or a material recovery system to reduce production cost and enhance customer satisfaction about environmental consciousness and to meet legal requirements. In our research, we designed a closed-loop supply chain which consists of recovery options such as collection centres and remanufacturing plants (reverse flow) in addition to traditional supply chain tiers (forward flow), and tried to find the best location for these facilities in a discrete space based on decision makers' opinions. Since there are uncertainties about decision parameters in an uncapacitated facility location problem, we implemented the fuzzy TOPSIS method to solve the location decision problem and find the best place to locate a remanufacturing facility.     

Evaluation and selection strategy for green supply chain using interval-valued q-rung orthopair fuzzy combinative distance-based assessment

Environment, Development and Sustainability - Environmental deterioration and global warming has created a substantial impact on international companies to incorporate eco-friendly, green supply...     

Developing a fuzzy linear programming model for locating recovery facility in a closed loop supply chain

In this research a closed loop supply chain is designed which incorporates reverse logistics and forward logistic system simultaneously. In the design of reverse logistic system, recovery options are embedded in traditional supply chain for treating returned products. The recovery system includes collection centres, remanufacturing plants and disposal centres. Since the product return is supply driven, there is an uncertainty about it. In the proposed configuration for closed loop supply chain, the optimised configuration for supply chain in terms of locating recovery plants is developed. Accordingly, a fuzzy mixed integer linear programming model develops to deal with the uncertainty of returning products by customers. A general-purpose solver (LINGO 8.0) and a Meta heuristic approach (genetics algorithm) are implemented to solve the proposed model. The answers are compared by defining indexes and then the optimal answer, configuration and variables are identified. This solution will suggest a new design of supply chain network in which waste of materials is minimised and the new raw materials are necessary only when the used products may not be recovered by recovery options.     

Sustainable EOQ and EPQ models for a two-echelon multi-product supply chain with return policy

Environment, Development and Sustainability - In this work, a new model is developed to determine optimum sustainable economic order quantity (EOQ) and economic production quantity (EPQ) values for...     

A robust multi-objective optimization model for project scheduling considering risk and sustainable development criteria

Environment, Development and Sustainability - There is limited research that considers the sustainability aspect of the projects’ schedule. The present study proposes a model to cover this...     

Closed-loop supply chain system with energy,transportation and waste disposal costs

Energy usage and consumption play important and strategic roles in modern manufacturing, inventory and logistics systems. The literature on inventory models for closed-loop supply chains reveals that, for no clear reasons, energy costs were ignored along with transportation and disposal costs. This paper introduces a closed-loop supply chain model that considers the economic value and energy content of products. It also offers a novel framework for studying lot-sizing policies of production processes in that context. Thus, a mathematical model for a closed-loop supply chain system with energy, transportation and disposal costs is developed. Numerical examples are provided with their results discussed. The developed model was also compared to that of Richter (1996) to stress the importance of accounting for the three noted costs. The numerical results emphasise that accounting for energy, transportation and disposal costs in supply chain modelling increases the sustainability of a production-inventory system due to the strong interdependence of the three costs on one hand, and their relationship to the environment on the other hand.     

A multi-path routing-inventory problem for a closed-loop supply chain considering the heterogeneous fleet of vehicles

In this paper, the inventory-routing problem is studied for a closed-loop supply chain. This closed-loop supply chain considers suppliers, manufacturers, whole-sellers, and disposal centers. To formulate this problem, a mixed integer linear programming model is proposed. This mathematical model minimizes the total costs of the supply chain, including the fixed and variable costs of vehicles, and holding inventory costs of final products and scraps. The proposed model considers the road roughness degree, multi-path setting and the heterogeneous fleet of vehicles, which increases its flexibility and the quality of solutions. Then, two symmetry-breaking constraints are proposed to reduce the complexity of the mathematical model. In order to evaluate the integrity of the proposed model, 20 instances of different sizes are randomly generated and solved. Finally, a comprehensive sensitivity analysis is conducted with respect to five key features of the problem, such as the impact of the symmetry-breaking constraints on the CPU time, multi-path setting, fixed cost of vehicles, heterogeneous fleet of vehicles, and lost sales. The results indicate that the consideration of multi-path setting and the heterogeneous fleet of vehicles improves the quality of solutions significantly.     

Supplier evaluation and selection for sustainable supply chain management under uncertainty conditions

Abstract

With the global increasing importance of sustainable development, sustainable supply chain has gained value among both researchers and industrialists in the last decade. Nowadays, industries are facing pressure from government legislation and the global competition in addition to the pressure from their clients to carry out environmentally – conscious actions. Thus, organisations are required to implement actions to enhance their level of both environmental and economic performances. Traditionally, organisations use criteria such as cost, quality and on-time delivery to evaluate their suppliers’ performance. Although there have been numerous studies on the common criteria for these assessments, very few studies have taken sustainable criteria into consideration. Thereupon, this study tries to put forward a complete model for selection and evaluation of the suppliers, considering three criteria for sustainability, thus using the fuzzy group graph theory and matrix approach. It is an innovative approach based on fuzzy logic and group decision-making, which aims to treat lack of certainty in selection and evaluation of suppliers. We will also discuss a case study in the industry to demonstrate the effectiveness of our proposed approach.     

Addressing food supply chain and consumption inefficiencies: potential for climate change mitigation

Globally, more than 30 % of all food that is produced is ultimately lost and/or wasted through inefficiencies in the food supply chain. In the developed world this wastage is centred on the last stage in the supply chain; the end-consumer throwing away food that is purchased but not eaten. In contrast, in the developing world the bulk of lost food occurs in the early stages of the supply chain (production, harvesting and distribution). Excess food consumption is a similarly inefficient use of global agricultural production; with almost 1 billion people now classed as obese, 842 million people are suffering from chronic hunger. Given the magnitude of greenhouse gas emissions from the agricultural sector, strategies that reduce food loss and wastage, or address excess caloric consumption, have great potential as effective tools in global climate change mitigation. Here, we examine the challenges of robust quantification of food wastage and consumption inefficiencies, and their associated greenhouse gas emissions, along the supply chain. We find that the quality and quantity of data are highly variable within and between geographical regions, with the greatest range tending to be associated with developing nations. Estimation of production-phase GHG emissions for food wastage and excess consumption is found to be similarly challenging on a global scale, with use of IPCC default (Tier 1) emission factors for food production being required in many regions. Where robust food waste data and production-phase emission factors do exist—such as for the UK—we find that avoiding consumer-phase food waste can deliver significant up-stream reductions in GHG emissions from the agricultural sector. Eliminating consumer milk waste in the UK alone could mitigate up to 200 Gg CO₂e year^?1; scaled up globally, we estimate mitigation potential of over 25,000 Gg CO₂e year^?1.     

Green product design in a supply chain with considering marketing under competition and coordination

Environment, Development and Sustainability - Environmental sustainability is becoming a leading indicator for evaluating supply chain management. This study considers two players, a manufacturer...     

生态文明阈值和绿值二步测度:指标-指数耦合链方法

拟破解生态文明测度和评价的现存难题:在指标选取方面,评价目标模糊,指标筛选的主观性强,缺乏结构化方法,导致指标泛化,与一般环境经济评价混淆;在测度标尺方面,无法确定生态文明阈值,对不同文明阶段用同一把尺子去衡量,导致一些非生态文明区域的排名反而靠前;在应用价值方面,综合指标值失去生态经济意义,只是一个抽象的排名数字,导致测度结果不便于理解和运用。为此,依据文明演化的共生理论创立指标-指数耦合链方法,用以导出生态文明测度的阈值和绿值二步指数。依次运用扎根理论法、PSIR及SEM结构模型、足迹家族法、Lotka-Volterra模型等工具,构建从生态文明的指标体系到二步指数的结构化耦合链。全过程始终聚焦生态文明的本质属性——产业与生态的互利共生性:以定性科学属性为出发点,以人与自然复合系统的结构模型为纽带,以生态文明阈值和绿值二步指数定量模型为归宿点。其中,阈值用产业受力指数、生态受力指数和共生度指数3项指数进行衡量,合称为阈值指数;而绿值用1项综合反映区域产业与生态的总量、共生程度和均衡程度的绿值指数进行衡量。据此进行区域生态文明的二步测度。第一步,基于阈值指数的阶段或资格判定:通过产业与生态的共生性,考量被测区域是否进入生态文明门槛,"未入门"区域处于哪一个文明阶段。第二步,基于绿值指数的水平判定:通过产业与生态的互利共生程度,考量"入门"区域的生态文明水平。研究表明,指标-指数耦合链方法不仅可以有效克服单纯指标体系综合法或指数函数法的缺陷和难点,而且能够将两者的长处结合起来。如此,不仅能够避免生态文明测度结果与物质文明"成正比"的弊端,而且能够通过从生态文明二步指数回溯至指标体系的逆向解耦,分析出导致生态文明问题的根本原因,便于提出切中肯綮的对策。     

A quantified model for assessment of drivers of acquiring green buildings by potential clients

Environment, Development and Sustainability - In the context of an ongoing crisis related to climate change resulting from human activities as well as global attempts to reverse or mitigate this...     

A new model for sustainable development: a case study of The Great Bear Rainforest regional plan

This paper describes a new model of sustainable development planning based on a case study of a successful planning process for the Great Bear Rainforest on Canada’s west coast. The planning region is an area of international ecological significance that contains one-quarter of the world’s remaining ancient coastal temperate rainforest. An innovative collaborative planning process was initiated in 1996 to develop a plan for the region that balances social, economic, and environmental values. The plan, which was accepted by consensus agreement of all stakeholders in 2006, uses a new model for sustainable regional development that is based on collaborative planning, collaborative implementation, informal conflict resolution, contextual adaptation incorporating comanagement with indigenous peoples (First Nations), joint fact finding, ecosystem-based management, and integration of social, economic, and environmental objectives.     

Urinary phthalate metabolite and bisphenol A associations with ultrasound and delivery indices of fetal growth

Growth of the fetus is highly sensitive to environmental perturbations, and disruption can lead to problems in pregnancy as well as later in life. This study investigates the relationship between maternal exposure to common plasticizers in pregnancy and fetal growth. Participants from a longitudinal birth cohort in Boston were recruited early in gestation and followed until delivery. Urine samples were collected at up to four time points and analyzed for concentrations of phthalate metabolites and bisphenol A (BPA). Ultrasound scans were performed at four time points during pregnancy for estimation of growth parameters, and birthweight was recorded at delivery. Growth measures were standardized to a larger population. For the present analysis we examined cross-sectional and repeated measures associations between exposure biomarkers and growth estimates in 482 non-anomalous singleton pregnancies. Cross-sectional associations between urinary phthalate metabolites or BPA and growth indices were imprecise. However, in repeated measures models, we observed significant inverse associations between di-2-ethylhexyl phthalate (DEHP) metabolites and estimated or actual fetal weight. An interquartile range increase in summed DEHP metabolites was associated with a 0.13 standard deviation decrease in estimated or actual fetal weight (95% confidence interval = − 0.23, − 0.03). Associations were consistent across different growth parameters (e.g., head circumference, femur length), and by fetal sex. No consistent associations were observed for other phthalate metabolites or BPA. Maternal exposure to DEHP during pregnancy was associated with decreased fetal growth, which could have repercussive effects.     

A new conceptual model for quantifying transboundary contribution of atmospheric pollutants in the East Asian Pacific rim region

Transboundary transport of air pollution is a serious environmental concern as pollutant affects both human health and the environment. Many numerical approaches have been utilized to quantify the amounts of pollutants transported to receptor regions, based on emission inventories from possible source regions. However, sparse temporal–spatial observational data and uncertainty in emission inventories might make the transboundary transport contribution difficult to estimate. This study presents a conceptual quantitative approach that uses transport pathway classification in combination with curve fitting models to simulate an air pollutant concentration baseline for pollution background concentrations. This approach is used to investigate the transboundary transport contribution of atmospheric pollutants to a metropolitan area in the East Asian Pacific rim region. Trajectory analysis categorized pollution sources for the study area into three regions: East Asia, Southeast Asia, and Taiwan cities. The occurrence frequency and transboundary contribution results suggest the predominant source region is the East Asian continent. This study also presents an application to evaluate heavy pollution cases for health concerns. This new baseline construction model provides a useful tool for the study of the contribution of transboundary pollution delivered to receptors, especially for areas deficient in emission inventories and regulatory monitoring data for harmful air pollutants.     

A new generic sub-model for radionuclide fixation in large catchments from continuous and single-pulse fallouts, as used in a river model

This paper presents a new general sub-model for fixation in catchment areas to be used within the framework of a river model for substances such as radionuclides and metals from continuous and single-pulse fallouts. The model has been critically tested using data from 27 European river sites covering a very wide geographical area and contaminated by radiocesium and radiostrontium from the Chernobyl accident and from the nuclear weapons tests (NWT fallout). This modelling approach gives radionuclide concentrations in water (total, dissolved and particulate phases) at defined sites on a monthly basis. The overall river model is based on processes in the upstream river stretch and in the catchment area. The catchment area is differentiated into inflow (approximately dry land) areas and outflow (approximately wetland) areas. The model has a general structure, which can be used for all radionuclides or substances. It is simple to apply in practice since all driving variables may be readily accessed from maps and standard monitoring programs. The driving variables are: latitude, altitude, catchment area, mean annual precipitation and fallout. Note that for large catchments, this model does not require data on the characteristic soil type or the percentage of outflow areas (wet lands) in the catchment, as in most previous models, since in practice it is very difficult to obtain reliable data on characteristic soil type or percentage of outflow areas, especially in large and topographically complex catchments. Modelled values have been compared to empirical data from rivers sites covering a wide domain (catchment areas from 3000 to 3,000,000 km2, precipitation from 400 to 1700 mm/year; fallouts from 1600 to 280,000 Bq/m2; altitudes from 0 to 1000 m.a.s.l. and latitudes from 41 degrees to 72 degrees N). The river model with its sub-model for fixation predicts close to the uncertainty factors given by the empirical data, which have been shown to be about a factor of 1.6 for 137Cs and a factor of 2.2 for 90Sr in river water. The obtained characteristic uncertainty factors for 137Cs from the Chernobyl fallout is 2.4, for 137Cs from the NWT fallout it is 1.3 and for the 90Sr results from the NWT fallout it is 3 using the new model.     

A model and design equations for the intermittent sand filter

Design parameters based upon influent suspended (SS) and volatile suspended solids (VSS) concentrations and hydraulic loading rates were evaluated. Functional relationships and coefficients describing the efficiency of the ISF process were developed based upon laboratory data from filter units containing 0.17 mm effective sand size (ε′) media. Adequate SS and VSS removals were observed for the 0.17 mm ε′ sand filters. Field data from other studies using filter units containing 0.17, 0.40, and 0.68 mm ε′ sand were also evaluated using the model. Sand sizes larger than 0.17 mm ε′ did not produce effluents satisfying a federal secondary standard of 30 mg/1 of SS when the filter influent suspended solids were predominantly algae.     

A new general dynamic model predicting radionuclide concentrations and fluxes in coastal areas from readily accessible driving variables

This paper presents a general, process-based dynamic model for coastal areas for radionuclides (metals, organics and nutrients) from both single pulse fallout and continuous deposition. The model gives radionuclide concentrations in water (total, dissolved and particulate phases and concentrations in sediments and fish) for entire defined coastal areas. The model gives monthly variations. It accounts for inflow from tributaries, direct fallout to the coastal area, internal fluxes (sedimentation, resuspension, diffusion, burial, mixing and biouptake and retention in fish) and fluxes to and from the sea outside the defined coastal area and/or adjacent coastal areas. The fluxes of water and substances between the sea and the coastal area are differentiated into three categories of coast types: (i) areas where the water exchange is regulated by tidal effects; (ii) open coastal areas where the water exchange is regulated by coastal currents; and (iii) semi-enclosed archipelago coasts. The coastal model gives the fluxes to and from the following four abiotic compartments: surface water, deep water, ET areas (i.e., areas where fine sediment erosion and transport processes dominate the bottom dynamic conditions and resuspension appears) and A-areas (i.e., areas of continuous fine sediment accumulation). Criteria to define the boundaries for the given coastal area towards the sea, and to define whether a coastal area is open or closed are given in operational terms. The model is simple to apply since all driving variables may be readily accessed from maps and standard monitoring programs. The driving variables are: latitude, catchment area, mean annual precipitation, fallout and month of fallout and parameters expressing coastal size and form as determined from, e.g., digitized bathymetric maps using a GIS program. Selected results: the predictions of radionuclide concentrations in water and fish largely depend on two factors, the concentration in the sea outside the given coastal area and/or adjacent coastal areas and the ecological half-life of the radionuclide in the sea. Uncertainties in these factors generally dominate all other uncertainties, e.g., concerning the surface water retention time, the settling velocity of the particulate fraction, the distribution coefficient regulating the fluxes in dissolved and particulate phases, the catchment area influences and the factors regulating biouptake and excretion of the radionuclide in fish. This means that the conditions in the sea are of paramount importance for the conditions in the coastal area, even for relatively enclosed coastal areas. This coastal model may be regarded as a tool for testing working hypotheses on the relative roles of different processes in different coastal areas. Such information is essential for getting realistic expectations of various remedial measures, such as coastal dredging discussed in this work.     

A new general mechanistic river model for radionuclides from single pulse fallouts which can be run by readily accessible driving variables

This paper presents a new general, process-based river model for substances such as radionuclides from single pulse fallouts. The new model has been critically tested using data from 13 European rivers contaminated by radiocesium from the Chernobyl accident. This modelling approach gives radionuclide concentrations in water (total, dissolved and particulate phases; and also concentrations in sediments and fish, but the latter aspects are not discussed in this paper) at defined river sites. The model is based on processes in the upstream river stretch and in the upstream catchment area. The catchment area is differentiated into inflow ( approximately dry land) areas and outflow ( approximately wetland) areas. The model also accounts for time-dependent fixation of substances in the catchment. The catchment area sub-model is based on a previous catchment model, which has been tested with very good results for radiocesium, radiostrontium and Ca-concentrations (from liming operations). The new river model is simple to apply in practice since all driving variables may be readily accessed from maps and standard monitoring programs. The driving variables are: latitude, altitude, continentality, catchment area, mean annual precipitation, soil type (percentages or organic and sandy soils), fallout and month of fallout. Modelled values have been compared to independent empirical data from 10 rivers sites (91 data on radiocesium in water) covering a wide domain (catchment areas from 4000 to 180 000 km(2), precipitation from 500 to 960 mm/yr and fallout from 1700 to 660 000 Bq/m(2)). The new model predicts very well--when modelled values are compared to empirical data, the slope is perfect (1.0) and the r(2)-value is 0.90. This is good giving the fact that there are also uncertainties in the empirical data, which set a limit to the achieved predictive power, as expressed by the r(2)-value.