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Closed-loop supply chain networks are gaining research popularity due to environmental, economic and social concerns. Such networks are primarily designed to overcome carbon footprints and to retrieve end of life products from customers. This study considers a multi echelon closed-loop supply chain in the presence of machine disruption. A multi-objective model is presented to optimize the total cost, the total time and emissions in a closed-loop supply chain network. The aim is to analyze the trade-off between the objectives of cost, time, and emissions and how these decisions are impacted by the selection of different available machines. A number of solution approaches are tested on a case study from the tire industry. The results suggest the improved performance of the hybrid heuristic and the importance of controlling disruption in a closed-loop supply chain network. Furthermore, there is a trade-off between the different objective functions which can help the decision maker to choose a particular solution according to the preference of an organization. Finally, conclusion and future research avenues are provided.

Despite the large quantities of secondary materials flowing within the built environment, their actual volume and respective waste management processes are not accurately known and recorded. Consequently, various sustainability and material efficiency policies are not supported by accurate data and information-reporting associated with secondary materials’ availability and sourcing. Many recent studies have shown that the integration of digital technologies such as city information management (CIM), building information modeling (BIM), and blockchain have the potential to enhance construction waste management (CWM) by classifying recycled materials and creating value from waste. However, there is insufficient guidance to address the challenges during the process of CWM. Therefore, the research reported in this paper aims to develop a blockchain-enhanced construction waste information management conceptual framework (BeCW). This paper is the first attempt to apply the strengths of integrated information-management modeling with blockchain to optimize the process of CWM, which includes a WasteChain for providing a unified and trustworthy credit system for evaluating construction-waste-recyclability to stakeholders. This is enabled through the use of blockchain and self-executing smart contracts to clarify the responsibility and ownership of the relevant stakeholders. As a result, this study provides a unified and explicit framework for referencing which quantifies the value-contribution of stakeholders to waste-recovery and the optimization of secondary construction materials for reuse and recycling. It also addresses the issue of sustainable CWM through information exchange at four levels: user, application, service, and infrastructure data levels.

Informal Green Spaces (IGS) in towns and cities are areas of varied appearance, representing a wide range of aesthetic values. In this study, we have focused on how users perceive such space and which elements match some particular values. Based on the analysis of photographic images taken by chosen IGS visitors, the technique called Visitor-Employed Photography (VEP), we elicited three primary groups of IGS images, namely landscape, scenery, and special elements. It is possible to define several visual structures in each category, with highly preferable spatial fragments and particular attributes. They are aesthetic prototypes, centers of aesthetic preferences among users of informal green areas. Recognizing proximity to the preference core allows us to define the preferred IGS landscape aesthetics. Based on the data collected, we have concluded that IGS users prefer vast grass areas, dense groups of trees and shrubs, water, and the absence of anthropogenic elements.

Existing frameworks for biophilic design have similar strategies and attributes as useful checklists for designers; however, the focus has been on adults rather than children, and there remains the need for more guidance related to school design by extension. The application of biophilia would be a design resolution in schools because of its impact on children’s health and well-being, which has been more important since the pandemic started; however, it remains quite unexplored in school design in many countries, including the UK. Biophilic design patterns can be used in school buildings and grounds for greater connectivity between spaces and nature in order to promote children’s well-being. This paper focuses on ten biophilic design patterns under two categories of ‘nature in the space’ and ‘natural analogues.’ This study presents the findings of case studies in various countries. The analysis focuses on the manifestations of biophilia to inform the application of biophilic design patterns for primary schools. Finally, this paper suggests how primary school children could be involved in a co-design process in order to evaluate biophilic design patterns.

There has been an emerging interest in the study of urban design dimensions associated with Transit-Oriented Developments (TODs). However, addressing the question of how TOD principles laid out in the international literature can be explored in the context of the global South remains in an incipient stage. In this paper, we investigate the nexus between station walkable catchments and forms of urbanity around transit nodes by adopting an assemblage approach to cut across any separation of sociality and spatiality. Drawing on empirical research from two case studies in Tehran, this paper contributes to studies on transit urban design by developing two measures of accessibility—the Catchment of Accessible Public Spaces (CAPS) and Accessible Interfaces (AI). We found that the combination of high CAPS and high AI within a given time can enable streetlife intensity, which is also linked to a synergistic effect of a larger assemblage, including the number of entries and diversity of functions. We argue that a focus on both measures is critical to understand the performance and potential transformation of street networks in a TOD.

Due to multiple properties, the international crude oil price is influenced by various and complex interrelated factors from different determinants in different periods. However, the previous studies on crude oil price fluctuation with economic policy uncertainty (EPU) haven’t taken a wider range of volatility sources into their analysis frameworks. In this paper, the time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model is introduced in order to avoid important information loss, as well as capture the time-varying impact on crude oil price fluctuation by EPU. Furthermore, the differences on crude oil fluctuations from net-oil exporting and net-oil importing country’s EPU are also elaborated. Here are three findings as follows. First, the impacts of global EPU on the crude oil price volatility show time-varying characteristics both in time duration and time-points. Second, the instantaneous impacts of global EPU on the price volatility of crude oil are directly relevant to major events, and the impacts are different in event types as well. Third, the time-varying characteristics depicting the impacts of EPU in countries who are net-oil exporter and net-oil importer on price volatility of crude oil show heterogeneity in fluctuation range, fluctuation intensity, and stage.

To increase the spatial resolution of Soil Moisture Active Passive (SMAP), this study modifies the downscaling factor model based on the Temperature Vegetation Drought Index (TVDI) using data from the Project for On-Board Autonomy (PROBA-V). In the modified model, TVDI parameters were derived from the temperature-vegetation space and the Enhanced Vegetation Index (EVI). This study was conducted in the north China region using SMAP, PROBA-V, and Moderate Resolution Imaging Spectroradiometer satellite images. The 9-km spatial resolution SMAP data was downscaled to 0.3-km spatial resolution soil moisture using a modified downscaling method. Downscaling accuracies from the original and modified downscaling factor models were compared based on field observations. The results show that both methods generated similar spatial distributions in which soil moisture estimates increased as vegetation coverage increased from built-up areas to forest. However, based on the root mean square error between observations and estimations, the modified model demonstrated an increased estimation accuracy of 4.2% for soil moisture compared to the original method. This study also implies that downscaled soil moisture shows promise as a data source for subsequent watershed scale studies.

A traditional logistics decision model mainly studies the location decision of logistics distribution centers, storage inventory management, vehicle scheduling, and transportation routes. The logistics location-inventory-routing problem (LIRP) is an integrated optimization of the three problems—a comprehensive optimization problem for the whole logistics system. This review paper uses the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method to review the literature on LIRP systematically. A total of 112 LIRP-related studies published between 2010 and 2021 are reviewed and classified based on 10 abstract and citation databases. The classification includes four aspects: problem characteristics, demand data types, model-based solutions, and application fields. From this systematic review, a few observations are recorded. First, the most popular problems among researchers are the multi-period multi-product problem, the multi-echelon single-link problem, and the multi-depot multi-retailer problem. Based on the objective function, the minimization of total supply chain cost is the primary concern of the LIRP literature. Researchers also favor other problem characteristics such as multi-objective programming, inventory control replenishment policy, and a homogeneous fleet of vehicles. We found that stochastic data are a common factor in an uncertain environment and have broad coverage. When dealing with the LIRP, heuristic and metaheuristic algorithms are the most widely used solution methodologies in the literature. In the application field of LIRP, the perishable products logistics network is mentioned in most applications. Finally, we discuss and emphasize the challenges of and recommendations for future work. This paper provides a systematic review of the literature on LIRP based on the PRISMA method, which contributes vital support and valuable information for researchers interested in LIRP.