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To avoid sub-optimization in wheat storage centers, one of the most strategic facilities, it is necessary to review and relocate them to be optimized regularly. The present study aims to propose an integrated method using geographic information systems (GISs) and an appropriate weighting algorithm for the relocation of wheat storage facilities.

To achieve the goal mentioned above, sustainability pillars in facility location and relocation are initially developed; afterward, a set of suitable criteria are obtained from various scientific resources. Then, the weight of each sustainable development pillar and its corresponding sub-criteria were identified through utilizing the best–worst method (BWM). By applying the obtained weights in the ArcGIS software package, various geographical layers were designed, and land-use planning, logistics planning and sustainable logistics planning are carried out in the regions. The regions are ranked based on the scores obtained in the processes, and the best regions are selected for sustainable relocation problem.

A case study including 430 regions (counties) in Iran is conducted to evaluate the efficiency of the suggested approach. The study results indicate that Iran possesses a superior state for establishing wheat storage centers in terms of infrastructural and social aspects. Also, it is established that 16% of counties are recognized as sustainable locations for relocating the wheat storage facilities.

There is no most suitable analysis of the wheat storage facilities, as well as their strategic position in the supply chain, and there is a lack of considering sustainability in wheat storage facility location, despite the particular importance of it to the supply chain.

This framework is applied in an Iranian wheat-bread supply chain to find the best sustainable facilities. It is noted that this algorithm can be applied in other strategic facilities by minor and some major changes.

Decision-makers can apply the proposed methodology to find the best relocation sites for wheat storage facilities as the main part of wheat-bread supply chain in order to prevent sub-optimization and improve the efficiency of their supply chain.

The purpose of this paper is to find a sustainable facility location solution for a closed-loop distribution network in the uncertain environment created by of high levels of product returns from online retailing coupled with growing pressure to reduce carbon emissions.

A case study approach attempts to optimize the distribution centre (DC) location decision for single and double hub scenarios. A hybrid approach combining centre of gravity and mixed integer programming is established for the un-capacitated multiple allocation facility location problem. Empirical data from a major national UK retail distributor network is used to validate the model.

The paper develops a contemporary model that can take into account multiple factors (e.g. operational and transportation costs and supply chain (SC) risks) while improving performance on environmental sustainability.

Based on varying product return rates, SC managers can decide whether to choose a single or a double hub solution to meet their needs. The study recommends a two hub facility location approach to mitigate emergent SC risks and disruptions.

A two-stage hybrid approach outlines a unique technique to generate candidate locations under twenty-first century conditions for new DCs.

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.

As in line with eco benchmarking, the purpose of this paper is to solve a location selection problem in an emerging country by applying sustainability benchmarking principles.

A hybrid multi-criteria decision-making method, fuzzy AHP and Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), is used as methodology to make sustainability benchmarking for logistics center location selection.

It is revealed that according to AHP and PROMETHEE calculations, Kemalpasa is determined as the most appropriate location from the sustainable perspectives. Torbali is specified as the worst location to construct a logistics center in terms of benchmarking criteria based on sustainability concerns. Based on these numerical results, managerial implications are presented with a sustainability benchmarking view.

The main originality of this study is integrating one of the relatively new topics, sustainability benchmarking, with a popular area, logistics center location selection.

This paper aims to study the hub transportation system in supply chain networks which would contribute to reducing costs and environmental pollution, as well as to economic development and social responsibility. As not all customers tend to buy green products, several customer groups should be considered in terms of need type.

In this paper, a multi-objective hub location problem is developed for designing a sustainable supply chain network based on customer segmentation. It deals with the aspects of economic (cost reduction), environment (minimizing greenhouse gas emissions by the transport sector) and social responsibility (creating employment and community development). The epsilon-constraint method and augmented epsilon-constraint (AEC) method are used to solve the small-sized instances of this multi-objective problem. Due to the non-deterministic polynomial-time hardness of this problem, two non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective grey wolf optimizer (MOGWO) metaheuristic algorithms are also applied to tackle the large-sized instances of this problem.

As expected, the AEC method is able to provide better Pareto solutions according to the goals of the decision-makers. The Taguchi method was used for setting the parameters of the two metaheuristic algorithms. Considering the meaningful difference, the MOGWO algorithm outperforms the NSGA-II algorithm according to the rate of achievement to two objectives simultaneously and the spread of non-dominance solutions indexes. Regarding the other indexes, there was no meaningful difference between the performance of the two algorithms.

The model of this research provides a comprehensive solution for supply chain companies that want to achieve a rational balance between the three aspects of sustainability.

The importance of considering customer diversity on the one hand and saving on hub transportation costs, on the other hand, triggered us to propose a hub location model for designing a sustainable supply chain network based on customer segmentation.

The research in competitive facility location (CFL) is quite dynamic, both from a problem formulation and an algorithmic point of view. Research direction has changed immensely over the years to address various competitive challenges. This study aims to explore CFL literature to highlight these research trends, important issues and future research opportunities.

This study utilises the Scopus database to search for related CFL models and adopts a five-step systematic approach for the review process. The five steps involve (1) Article Identification and keyword selection, (2) Selection criteria, (3) Literature review, (4) Literature analysis and (5) Research studies.

The paper presents a comprehensive review of CFL modelling efforts from 1981 to 2021 to provide a depth study of the research evolution in this area. The published articles are classified based on multiple characteristics, including the type of problem, type of competition, game-theoretical approaches, customer behaviour, decision space, type of demand, number of facilities, capacity and budget limitations. The review also highlights the popular problem areas and dedicated research in the respective domain. In addition, a second classification is also provided based on solution methods adopted to solve various CFL models and real-world case studies.

The paper covers 40 years of CFL literature from the perspective of the problem area, CFL characteristics and the solution approach. Additionally, it introduces characteristics such as capacity limit and budget constraint for the first time for classification purposes.

Refugee camps are not easily welcomed by local communities. The purpose of this paper is to outline a structured approach to support the decision-making process for siting refugee camps in mainland Greece using multiple criteria, including local opposition. A suitability analysis generates a list of potential sites and a multiple criteria evaluation is applied. The motivation is the development of a methodology that can support choices and policies regarding the refugee camps siting problem, incorporating the need to address local opposition.

The proposed methodology combines geographic information systems (GIS) with multiple criteria decision-making (MCDM) techniques. These are used to develop a location classification and ranking model based on related criteria and subcriteria, attributes and weights. The region of Peloponnese in Greece is selected as a case study to validate the approach.

The lack of predefined candidate sites for refugee camps necessitates, initially, tackling a site search problem to generate a pool of potential sites through a suitability analysis. Subsequently, using the GIS the pool yields a subset of potential sites, satisfying all the criteria to setup a refugee camp. Through the current analysis the suitability of the single existing refugee camp site in Peloponnese can be evaluated. Finally, a “with and without” analysis, excluding the social criterion, depicts the changes in the candidate sites pool and their scores.

There is a lack of relevant literature taking into account the local opposition or sociopolitical implications as decision criteria. The selection of the appropriate criteria is a complex process that involves the cooperation of many experts. The main criteria, subcriteria and their attributes were determined according to existing literature and authors' informed judgment.

The proposed methodology can help decision-makers to setup a decision-making system and process for identifying refugee camps' sites using multiple criteria, including local opposition.

The Middle East and North Africa (MENA) region is known for its extreme weather conditions during Summer. A major determinant of the sustainability of the design of a building is its fenestrations. The purpose of this paper is to explore the problem of designing and locating windows on building facades such that a number of relevant criteria to the MENA region are optimised, including solar heat gain, privacy, daylighting and cost of installation.

A multi-objective optimisation problem is proposed with the focus on capturing the requirements of residential dwellings in the MENA region. Since the problem contains conflicting objectives that need to be optimised, a lexicographic approach is adopted. In order to display the Pareto curve, a bi-objective analysis based on the ε-constraint method is utilised.

The conflicting nature of the proposed problem is indicated via the Pareto optimal solutions yielded. Depending on the preference of criteria adopted in lexicographic optimisation, the location of the windows on the building façade tends to change. The bi-objective analysis indicates the importance of balancing out the daylight factor against each of privacy, solar heat gain and installation cost criteria. Furthermore, an analysis conducted in three major cities in the MENA region highlights the discrepancy in design alternatives generated depending on the local climatic condition.

This work proposes a novel mathematical optimisation model which focuses on producing a sustainable design and layout for windows on the facades of residential dwellings located in the MENA region. The proposed model provides designers with guidance through an automated support tool that yields optimised window designs and layout to ensure the sustainability of their designed buildings.

The research article's primary purpose is to understand the advancements in urban logistics and allied fields over time along with a consideration of its enabling technologies.

An initial review is used to build a keyword vocabulary, combinations of which were then applied to the Scopus, ScienceDirect, Emerald Insights, the Web of Science (WOS), Elsevier, Taylor and Francis, Wiley, Inderscience, Springer, Google Scholar and IEEE Xplore for extracting academic publication collection. The first part includes bibliometric analysis; network analysis is done based on the finally selected 645 papers (only those articles include either of the keywords mentioned above in title, abstract, and keywords). The second part conducts a review of the existing literature review studies (only 21 literature review studies out of 645 articles). The last one discusses the advancement in the topics based on the selected research articles.

This research discussed the advancement of the urban logistics and allied field, key academic forums and key researchers. It is evident from the analysis that the research related to key emerging themes like implementing innovative concepts and sustainability; application of green technologies; data collection, visualization, monitoring and sharing; and automatic logistic systems are still in the nascent stage. However, these research areas gained momentum in the recent past.

Urban logistics are essential and play a crucial role for such rapidly growing cities to function. Despite playing a vital role, urban ecosystem logistics is often neglected in formal urban planning. Hence, as a response to customer and business demand, private entities regularly invest in new technologies and solutions. Since such investments are toward profits, various environmental, social and economic challenges arise.

This research investigates the advancements in urban logistics toward smart, sustainable reforms in developing enabling technologies and markets. The obtained research articles are subjected to bibliometric, descriptive, network and content analysis to present a rundown of advancements, relationships and trends in emerging research gaps.

Through an empirical study, this research proposes a multi-dimensional assessment method for Sustainable Building Design (SBD). This approach is adopted to investigate and evaluate the current practices of SBD and to provide a basis for refining such processes while reducing existing shortfalls. In doing so, a holistic sustainable framework for rating the sustainable performance of buildings is proposed.

To achieve the aforementioned purpose, this research (1) investigates the most current trends in SBD including the use of Building Information Modelling (BIM); (2) examines the practical issues of SBD; (3) proposes a multi-dimensional assessment method; and (4) compares 18 separate case studies in the three countries of Australia, United Kingdom and USA, as part of the SBD implementation. To compare these case studies, an additional SBD tool, Green Building Rating and Certification System (GBELS) was carefully selected and applied. Five core values of SBD were identified based on functionality, accessibility and productivity, which align with the GBELS outcomes.

This research found that, for the 18 examined buildings, the main issues in SBD in the three countries concerned environmental and ecological issues. These included the impacts of buildings on the environment, as well as issues concerning the buildings' life cycle analysis and assessment. It was also determined that energy usage, pollution reduction and climate change concerns were important inclusions in establishing these buildings, particularly in the USA.

To support the research aim, this paper explores the most innovative trends in SBD assessments including their Structural Health Monitoring (SHM), grade (stars) classification, Relative Weight (RW) and particularly GBELS. GBELS was selected for this research, since it is relatively new and there is little available literature discussing its adaptation. Accordingly, this research further evaluates the application of GBELS as a part of versatility in SBD multi-dimensional assessment method. As the basis of these tests, a total of 18 separate case studies are closely evaluated.