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Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

A sustainable selection method for facility location of the water treatment is formulated by best–worst method. In addition, the model addresses the selection of appropriate technologies in the treatment plant, management of water leakage in the whole transmission network by using modernization and selection of different transmission technologies. Finally, the interaction between water and energy in this network seems to be paying particular attention.

Rapid population growth and urban development, and the constraints of water supply have become one of the crucial challenges around the world in the 21st century. Hence, the use of refined urban wastewater is increasing in many countries as an alternative source of water. In this regard, the rehabilitation of urban wastewater recycling and reuse has been proposed as one of the most suitable solutions for urban water management. Hence, in this paper, a mathematical model is formulated to design the simultaneous marketing of the urban water distribution network and wastewater treatment (including).

It seeks to ensure that energy is supplied through chemical methods to ensure that the system's energy dependence is on the national electricity grid. And in order to validate the model, a case study has been studied. By analyzing the results, it can be concluded that the upgrading of sewage treatment plants to replace underground water and water from nearby dams in household, agricultural and industrial applications will have positive environmental and economic impacts. One of the notable environmental impacts is the decline in groundwater and water scarcity in the coming years.

The summary of contributions is presented follow as: design and planning of water and urban wastewater integrated network; sustainable selection of facility location for the water treatment; capability selecting different treatment technologies in simultaneous design water and urban sewage supply chain; managing water leak in the network; proposed a water–energy nexus model in simultaneous design water and urban sewage supply chain; studying the feasibility of construction of power plants from biogas, the resulting of anaerobic digestion in treatment centers.

The purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance.

The best-worst method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance.

The proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% and 70% throughout the year. Management performance can be seen high in the 1st and 2nd quarter of the financial year ranging from 70% to 80%, whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year.

This paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application.

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

This study aims to develop a new design for the fluid-safety valve to make it more environmentally friendly.

Computational fluid dynamics is carried out to analyse the behaviour of flow in both traditional and new safety valves.

The possibility of failure in the new design under the maximum allowable working pressure is analysed using finite element analysis.

Investigating a new low-fluid pressure safety valve design.

Green economy and economic development with high quality have set higher requirements for the development of the urban logistics industry. It can grasp the recent development level of the urban logistics industry by measuring its environmental efficiency to guide its future development direction. The purpose of this study is to improve the environmental efficiency and development level of the urban logistics industry by using a reasonable evaluation method.

This paper uses information entropy to directly aggregate index weights from different models to acquire comprehensive index weights (CIWs) for calculating peer-evaluation efficiency. Then, we weight self and peer-efficiencies to obtain final efficiency. The environmental efficiencies of the urban logistics industry in Anhui Province in 2019 are obtained according to the above method.

Several findings are summarized below. The logistics industry in Anhui is in urgent need of improving environmental efficiency. The environmental efficiency of the logistics industry in North Anhui is the highest one, showing that the logistics industry in North Anhui has achieved a relative balance between economic development and environmental protection. Their final cross-efficiency values based on the CIWs are smaller than those based on the comprehensive efficiency. And the environmental efficiency of almost all urban logistics industries is lower than its economic efficiency. The findings show that the proposed method is feasible and more reasonable. More economic implications and suggestions are proposed.

This paper proposes an extended cross-efficiency evaluation method based on information entropy to measure the environmental efficiency of the urban logistics industry, effectively avoiding the overestimation of efficiency results.

The purpose of this paper is to investigate the heat transfer of laminar and turbulent pulsating Al203/water nanofluid flow in a two-dimensional channel. In the laminar flow range, with increasing Reynolds number (Re), the velocity gradient is increased. Also, the Nusselt number (Nu) is increased, which causes increase in the overall heat transfer rate. Additionally, in the change of flow regime from laminar to turbulent, average thermal flux and pulsation range are increased. Also, the effect of different percentage of Al₂O₃/water nanofluid is investigated. The results show that the addition of nanofluids improve thermal performance in channel, but the using of nanofluid causes a pressure drop in the channel.

The pulsatile flow and heat transfer in a two-dimensional channel were investigated.

The numerical results show that the Al₂O₃/Water nanofluid has a significant effect on the thermal properties of the different flows (laminar and turbulent) and the average thermal flux and pulsation ranges are increased in the change of flow regime from laminar to turbulent. Also, the addition of nanofluid improves thermal performance in channels.

The originality of this work lies in proposing a numerical analysis of heat transfer of pulsating Al₂O₃/Water nanofluid flow -with different percentages- in the two-dimensional channel while the flow regime change from laminar to turbulent.

The purpose of this study is to investigate the pulsating flow in a three-dimensional channel. Channel flow is laminar and turbulent. After validation, the effect of different channel cross-sectional geometries (circular, hexagonal and triangular) with the pulsating flow are investigated. For this purpose, the alumina nanofluid was considered as a working fluid with different volume percentages (0 per cent [pure water], 3 per cent and 5 per cent).

In this study, the pulsatile flow was investigated in a three-dimensional channel. Channel flow is laminar and turbulent.

The results show that the fluid temperature decreases by increasing the volume percentage of particles of Al₂O₃; this is because of the fact that the input energy through the wall boundary is a constant value and indicates that with increasing the volume percentage, the fluid can save more energy at a constant temperature. And by adding Al₂O₃ nanofluid, thermal performance improves in channels, but it should be considered that the use of nanofluid causes a pressure drop in the channel.

Alumina/water nanofluid with the pulsating flow was investigated and compared in three different cross-sectional channel geometries (circular, hexagonal and triangular). The effect of different volume percentages (0 per cent [pure water], 3 per cent and 5 per cent) of Al₂O₃ nanofluid on temperature, velocity and pressure are studied.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.