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• Development of a new MCDM method, named Stratified Best – Worst Method (SBWM). • Addressing sustainable waste disposal technology selection using SBWM. • Consideration of uncertainty and doubts in decision-making environment. • The proposed decision-making framework is used for a case study in Iran. • Comparative analysis for the proposed model. Waste disposal technology selection is a key problem in the field of municipal solid waste (MSW). This decision may have long-term impacts on environmental development and economic growth. The literature suggests using multi-criteria decision-making (MCDM) methods to address this problem. MCDM techniques commonly require decision makers to assign weightings of importance to the decision criteria based on which, the available technologies are ranked. However, this technology selection problem is concerned with selecting a technology to be used for a relatively long period of time. It is important to take into consideration any uncertainty the decision maker may have with regard to the weightings of the criteria in the future. To take this uncertainty into consideration, this study suggests utilizing a recently developed MCDM technique, namely the stratified MCDM. This technique is designed to help decision makers structure the uncertain future through the consideration of a set of states, which are placed in different strata. The paper shows how the stratified MCDM technique in combination with the best-worst method (labelled stratified BWM) can be employed to compute the ranking of the available technologies. This research is expected to stimulate future applications of the stratified BWM to facilitate long-term decision making. [ABSTRACT FROM AUTHOR]

The focus of this paper is on selecting suppliers in the Oil and Gas (O&G) industry by developing a comprehensive approach for Multi-Criteria Decision Analysis (MCDA) based on alternative methods capable of assessing different aspects of supplier selection uncertainty in terms of utility functions and criteria related to efficiency. The O&G industry has a key role in the public sector of various countries such as Iran with its revenues being of prime importance to develop infrastructure facilities such as for healthcare, education, and transportation. This comprehensive approach walks through various stages for selecting Critical Success Factors (CSFs), ranking suppliers, and for setting partial weighting alternatives. While CSFs are selected using a traditional Delphi approach, the partial supplier rankings are defined based on Complex Proportional Assessment (COPRAS) utility functions together with criteria weights derived from Step-wise Weight Assessment Ratio Analysis (SWARA) for each CSF. As it concerns information reliability of utility and efficiency functions of both methods obtained via expert preferences or perceptions, Z-numbers are used to address the intrinsic fuzziness level inherent to each analytical stage. Iran's economy depends on revenues from oil and other related production, which means that by earning more income from this industry, most of its economic indicators such as GDP and employment rate should increase significantly, thus leading to economic growth. Various countries put plans in place related to production for increasing their social economics. One of these plans is focused on suppliers since they have a high impact on providing essential items such as equipment, HR, and transportation, so by choosing the best suppliers in all fields, costs will decrease and consequently revenue will increase. This research points out how to rank O&G industry suppliers using MCDA methods in an uncertain environment. An example based on actual data from an Iranian O&G company is provided to show the applicability of the approach proposed. Results suggest that the complexity of O&G operations on selecting suppliers can be adequately handled by information reliability techniques applied to traditional economic concepts such as utility- and efficiency-related factors, particularly in business environments characterized by a trade embargo. • The paper focuses on selecting O&G suppliers using a comprehensive MCDM. • Alternative ranks are defined by COPRAS and criteria weights are defined by SWARA. • Z-numbers are used to address the intrinsic reliability level of each analytical stage. • Results suggest that information reliability of alternative suppliers and weights can represent complex environments. [ABSTRACT FROM AUTHOR]

Abstract: Futures Studies is a recent addition to the academic/intellectual/policy making life in Iran. Despite the fact that publication/launch dates of the first books/research projects on Futures Studies go back to few decades ago, it is only in the past few years that promotion of this discipline has gained momentum. Our aim in this paper is to present an overview of the development of Futures Studies in Iran since 1960s. We briefly explore the history of Futures Studies in Iran and explain why it has taken a technocratic line, as opposed to other possibilities (e.g. corporatist, environmentalists, citizen visioning (anticipatory democracy), etc.). In particular, we present an analysis of an ongoing and comprehensive foresight project whose objective is to provide Iranian top decision makers with a set of scenarios concerning future developments in a number of areas of science and technology until 2025. The main argument of the paper is that in response to the demands made by the policymakers, Iranian scholars, academics and technologists are trying to equip themselves with the latest techniques and know how for long-term planning and vision-building. However, due to various limitations the ride has not been an easy one. To overcome the obstacles, those who are at the forefront of developing indigenous versions of technological and theoretical aspects of Futures Studies have resorted to the method of trial and error and learning through doing. The paper critically examines the weaknesses and points of strength of this approach in the context of Iran. [Copyright &y& Elsevier]

Abstract An early-warning system is a general idea that can act as a functional and inexpensive tool to ease the access to the global strategic goals of protection and sustainable development. Before the crisis happens, this system can provide effective information by using known resources, which creates an awareness of probable dangers and necessary actions. This study proposes an optimal method to cover the shortages in protected-area management. The proposed early-warning system is based on the pressure-state-response (P-S-R) approach and ecological security index. Twelve environmental indicators in three different criteria (P = 4, S = 5, R = 3) were chosen and the ecological security index of the protected area was generated. Based on the ecological security index status in the study area, statistical analysis, and expert opinions, three indicators (precipitation, vegetation covering status, and soil brightness) were chosen as the main and final indicators, to be used in the early-warning system. Eventually, with the calculation of the thirty-year average of the mentioned indicators in the area under study, the confidence interval for each of these indicators with a confidence factor of 95% was achieved. According to the results of this research, some parts of the south-west and east of the area under study were in warning status, which requires special management decisions. Based on the field visit and expert review in these parts, there was an obvious breakdown in the selected indicators. In fact, we've prevented the ecological disturbance in the ecosystem which plays an important role in preserving species of international importance by using technologies. We've made a shortcut to achieve the managerial goals in less developed countries in further studies in this field; the importance of each early-warning system indicator can be determined, so warning regions can be divided into more categories. This research can be applied in other climates, and the result can be compared to this paper, but the choice of general and effective indicators remains the most important part of the approach reported here. [ABSTRACT FROM AUTHOR]

Abstract: As a key component of Iran’s urban policy and planning, new town development has been scrutinised from various aspects such as design and architecture, geography, and sociology, with much of the literature concentrating on the substantive challenges of the development process. Missing, however, is the account of its procedural challenges arising from the influential actors and factors involved in that process. This paper focuses on the critical assessment of the performance of the key factors and actors involved in the Iranian New Town development decisions. These modifications seem necessary, as will be argued, because due to weak governance, the new town development programme has not yet achieved all its goals. Part one of this paper discusses the planning framework of the Iranian New Towns; part two discusses the national and regional levels of urban planning in Iran, stressing the planning process and the actors involved; part three concentrates on master planning, and part four concludes with suggestions for improving the urban development process in Iran. [Copyright &y& Elsevier]

Abstract: One of the primary concerns on target setting the electricity distribution companies is the uncertainty on input/output data. In this paper, an interactive robust data envelopment analysis (IRDEA) model is proposed to determine the input and output target values of electricity distribution companies with considering the existence perturbation in data. Target setting is implemented with the uncertain data and the decision maker (DM) can search the envelop frontier and find the targets based on his preference. In order to search the envelop frontier, the paper combine the DEA and multi-objective linear programming method such as STEM. The proposed method of this paper is capable of handling uncertainty in data and finding the target values according to the DM’s preferences. To illustrate ability the proposed model, a numerical example is solved. Also, the input and output target values for some of the electricity distribution companies in Iran are reported. The results indicate that the IRDEA model is suitable for target setting based on DM’s preferences and with considering uncertain data. [Copyright &y& Elsevier]

Abstract: Information technology (IT) is a tool crucial for enterprises to achieve a competitive advantage and organizational innovation. A critical aspect of IT management is the decision whereby the best set of IT projects is selected from many competing proposals. The optimal selection process is a significant strategic resource allocation decision that can engage an organization in substantial long-term commitments. However, making such decisions is difficult because there are lots of quantitative and qualitative factors to be considered in evaluation process. This paper has two main contributions. Firstly, it combines two well-established managerial methodologies, balanced scorecard (BSC) and data envelopment analysis (DEA), and proposes a new approach for IT project selection. This approach uses BSC as a comprehensive framework for defining IT projects evaluation criteria and uses DEA as a nonparametric technique for ranking IT projects. Secondly, this paper introduces a new integrated DEA model which identifies most efficient IT project by considering cardinal and ordinal data. Applicability of proposed approach is illustrated by using real world data of Iran Ministry of Science, Research and Technology. [Copyright &y& Elsevier]

Abstract: In recent years, BOT approach has provided an increasingly popular project financing to move toward infrastructure development in Asian countries such as Iran. There are many complexities in projects because of the variety of factors in project’s trend and also the dependence of project on mainly national factors. Due to these complexities and their long-term operating, the projects meet with uncertainty and numerous risks. In this paper, an attempt is made at identifying common risks in BOT projects. A novel hierarchical structure of risks is presented on the basis of the project-oriented point of view; next, some effective criteria for risk ranking in BOT projects are introduced. Then, the problem is defined in Fuzzy Multi Attribute Decision Making (FMADM) field. Therefore, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) and Fuzzy Linear Programming Technique for Multidimensional Analysis of Preference (FLINMAP) methods are presented in order to rank high risks in BOT projects. In this study, these two methods are compared in four respects: separation among alternatives, fuzzy error in criteria’s weights, risk response planning, and numerousness of alternatives in proportion to criteria. The proposed model is used for identifying and assessing risks in Iran BOT power plant project. Finally, the rankings of high risks are determined according to their results at the end of this paper. [Copyright &y& Elsevier]

This paper examines the development of higher education in Iran during a 26-year period under the Islamic government. This can be divided into three different phases: revolutionary, formative and development. It explores the expansion of universities, enhancing research, widening access, use of a wide range of ICT, decentralisation and gender equity. The quality and relevance of curricula with the market requirement is also discussed. This paper argues that the curriculum should be more specific and address the real needs of society. Comprehensive decision-making, expanding students’ academic guidance and expanding participatory and student-centre environment in higher education are crucial. [Copyright &y& Elsevier]

A predominant characteristic of geotechnical works and more particularly tunneling projects, is the uncertainty that surrounds the geologic medium in which the construction is to be performed. This paper is dealing with the risk analysis of both the construction time and cost of a challenging part of Tehran Metro Line 7, an urban tunneling project which is currently being under development. The Decision Aids for Tunneling (DAT) has been utilized for this assessment, concerning the risk analysis by taking into account different scenarios relating to the measures implemented to prevent surface subsidence problems. The results have shown that selection of different sorts of methods will help control the risk of escalating the project’s total construction cost and time to completion. This research delivers useful information to concurrently help the owner, the contractor as well as the designer of the project in making the most appropriate decisions under such a highly uncertain and challenging geological environment. [ABSTRACT FROM AUTHOR]

Performance assessment of Iranian petrochemical companies based on the H3SE performance excellence model is the purpose of this paper. Reaching this goal, different aspects of the sustainable excellence model and its indices have been introduced, and through Multiple Attribute Decision-Making (MADM) approaches, Iranian petrochemical companies were assessed and ranked. Since the results of MADM are not panacea for all decision making problems and the questionnaire self-assessment approach is not rigorous enough, different techniques have been involved for compensation. In the following, the convergence of MADM rankings has been compared. The findings signify that processes management, leadership, social environmental accountability and staff results are of relative importance in H3SE performance assessment. Moreover, Ethylene Gharb, Zagros, and Bandar Imam companies have the highest rankings. Finally, ranking sensitivity was analyzed. Since the data were collected through questionnaire self-assessment approach, the reliability of this assessment may be doubted. [ABSTRACT FROM AUTHOR]

The multi criteria decision making (MCDM) has been applied in Integrated Energy Planning (IEP) and Integrated Coastal Management (ICM) frameworks. In this paper, a novel hybrid MCDM approach based on the fuzzy analytic network process (ANP), fuzzy decision making trail and evaluation laboratory (DEMATEL) and fuzzy elimination and choice expressing the reality (ELECTRE) methodologies is applied to assist in the site selection of offshore wind farm (OWF) as the renewable energy in the IEP and the ICM frameworks. The aim of this study is to find the best site selection of offshore wind farm for four sites (alternatives) in Bandar Deylam on the Persian Gulf in southwest of Iran. Six criteria (depths and heights, environmental issues, proximity to facilities, economic aspects, resource technical levels and culture) and the related sub-criteria are considered to select proper sites for power station of OWF. The fuzzy ANP method is employed for standpoints of the site selection (goal) subject to the criteria and is performed the criteria subject to the sub-criteria. In addition, due to considering the influences of the criterion to another criterion, the fuzzy DEMATEL is employed in criteria and sub-criteria sections. Moreover, the fuzzy ELECTRE is applied to calculate the decision making matrices of sub-criteria to alternatives. The results show that the alternative A 3 is the best site of OWF for Bandar Deylam. Then A 2 , A 4 are the best alternatives and finally alternative A 1 is the worst site. Also, a sensitivity analysis is performed to investigate the robustness of the outcomes of decision making by changing the priorities of the criteria. The results indicate the robustness of this method when the experts’ opinions subject to the criteria change. The evaluation criteria and this methodology could be applied to other coastal cities for promoting the progress of ICM towards the goal of sustainability. [ABSTRACT FROM AUTHOR]

One of the promising ways to shift towards sustainable development has been the utilization of solar energy worldwide. Based on its geographical specifications, Iran enjoys high solar potential to implement feasible solar energy projects. However, to obtain the best productivity and payback, identification and prioritization of suitable regions for construction of expensive solar power plants is a delicate issue. In contrast with common assumptions, identifying appropriate geographical regions for implementation of such projects is not only associated with the amount of received solar radiation, but also there are many economic, environmental, technical, social and risk criteria (and their relevant sub-criteria) which must be taken into account. To address the complicated nature of the prioritization challenge caused by existence of various indicators, this paper applies a hybrid Multi-Criteria Decision Making (MCDM) approach and prioritizes 25 scattered cities all around the country for implementation of future solar power plants. For this, both quantitative and qualitative effective indicators are identified to be considered as the inputs to the utilized hybrid model. The Step-wise Weight Assessment Ratio Analysis (SWARA, proposed in 2010) method is employed to rank the identified criteria, and the Weighted Aggregates Sum Product Assessment (WASPAS, proposed in 2012) is applied to evaluate and prioritize the alternatives (cities) where Yazd city ranked first. Eventually via considering the ranked cities, a comprehensive GIS map of the country is presented. The utilized integrated approach can offer helpful information for energy sector decision-makers and planning energy management in top level of managing requirements of countries in all respects. [ABSTRACT FROM AUTHOR]

• Proposing a model for power system vulnerability assessment under uncertainty. • Proposing a linear approximation for a mixed-integer trilevel nonlinear program. • Proving a lemma which makes our model efficient and much easier to solve. • Reformulating the original multilevel model as a single-level MILP model. • Solving the proposed MILP model efficiently using the off-the-shelf solvers. With the growing level of uncertainties in today's power systems, the vulnerability analysis of a power system with uncertain parameters becomes a must. This paper proposes a two-stage adaptive robust optimization (ARO) model for the vulnerability analysis of power systems. The main goal is to immunize the solutions against all possible realizations of the modeled uncertainty. In doing so, the uncertainties are defined by some pre-determined intervals defined around the expected values of uncertain parameters. In our model, there are a set of first-stage decisions made before the uncertainty is revealed (attacker decision) and a set of second-stage decisions made after the realization of uncertainties (defender decision). This setup is formulated as a mixed-integer trilevel nonlinear program (MITNLP). Then, we recast the proposed trilevel program to a single-level mixed-integer linear program (MILP), applying the strong duality theorem (SDT) and appropriate linearization approaches. The efficient off-the-shelf solvers can guarantee the global optimum of our final MILP model. We also prove a lemma which makes our model much easier to solve. The results carried out on the IEEE RTS and modified Iran's power system show the performance of our model to assess the power system vulnerability under uncertainty. [ABSTRACT FROM AUTHOR]

Nowadays, one of the growing and remarkable branches of tourism is ecotourism. Ecotourism has a great impact on the development of a region from different perspectives. Hence, by improving and developing sustainable ecotourism in a region, it will be possible to develop and improve its economic, social, and environmental situation. The Lafour region is one of the potential hubs for ecotourism activities in Iran. Despite the high potential of this region for ecotourism activities, it has not yet achieved its suitable position in this domain. Hence, the main goal of this study is to develop sustainable goals for ecotourism in the region. To meet the target, first, the Strengths, Weaknesses, Opportunities, and Threats (SWOT factors) are identified through interviews with tourists, local residents, and the experts, filed observation, and considering similar works in the literature review. Then, some practical and useful strategies are determined based on SWOT analysis and consulting with the experts. The important point of the study is proposing an applicable heuristic clustering method based on SWOT analysis to classify the strategies into different clusters. To prioritize the strategies in each cluster, the commonly used Multi-Criteria Decision Making (MCDM) method called the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is applied. This paper concludes and reveals that the three strategies including ST6 "Encouraging investors and entrepreneurs to establish ecotourism centers in the region", ST5 "Establishing and improving the hygiene units and the medical clinics in the region", and ST3 "Improving and diversifying tourism services and products to attract tourists and increase their satisfaction" have the greatest impact on accomplishing sustainable development goals in the region. • The main goal of this study is to develop sustainable ecotourism in Lafour region, Iran. • The SWOT are identified by the help of interviews with tourists, tourism experts, ecotourism activists, local residents and academic experts. • Eight strategies are determined based on SWOT analysis and consulting with tourism experts. • A heuristic clustering method based on SWOT analysis is proposed and the strategies are ranked to different clusters. • The strategies in each cluster are prioritized by TOPSIS method. [ABSTRACT FROM AUTHOR]

Abstract: Contribution to satisfying the final energy demand, the necessities arises from waste minimization, and rural area's developments are the main incentives for biofuel usage in the Iranian energy supply system. This paper develops a model for the supply chain of bioethanol and bioETBE from the farms to the end users which integrates the temporal and spatial scales. It considers the techno-economical evaluations of first and second generation biofuels. The results provide practical insights for decision makers to introduce the biofuel into the Iranian energy systems. Here, the optimal designs of transition pathways of biofuel supply chain are available which successfully assesses the benefits and barriers to the decision maker. [Copyright &y& Elsevier]

Abstract: This paper explores the applicability of transforming the current state of tourism in Boujagh National Park (BNP) (a region located in the northern Iran with an area of 3177ha) to a sustainable tourism model. To plan and implement this, different management and decision making tools were used including interviews and questionnaire surveys as well as SWOT analysis. A series of interviews was conducted in order to identify actions taken by governmental bodies responsible (e.g., Department of Environment). In addition, the visitors of the park were surveyed to assess the rate of fulfillment of sustainable tourism development in the park. Local residents were also taken into account by using a survey to reveal the problems and attractions of the park. Results showed that the existing tourism activities in the park did not conform to sustainability requirements. Thus, a SWOT analysis was used to identify the required management strategies to improve the tourism in the park. [Copyright &y& Elsevier]

Unplanned pumping of groundwater in the past two decades has caused many regional problems and tensions, leading to seawater intrusion into coastal aquifers. The main objective of this paper is the use of a Multi-Criteria Decision-Making (MCDM) approach combining with numerical simulation for reducing seawater intrusion in the Tajan coastal aquifer located on the southern seashores of the Caspian Sea, Iran, taking into account economic, social, and environmental issues. The MODFLOW code was used to simulate the groundwater flow. MT3DMS and SEAWAT codes were used to simulate the solute transport and seawater intrusion. A 10-year period from 2010 to 2020 was simulated for evaluating the current conditions and forecasting the future conditions of the aquifer. The results indicated an increase in the extent of seawater intrusion. To assess the proposed eleven curative solutions, the economic, social, and environmental criteria such as efficiency of applying of curative solutions in improvement of the aquifer's water level and efficiency of applying of curative solutions on reduction in the extent of the seawater intrusion were weighted using the Analytic Hierarchy Process (AHP) method. The results of the AHP method showed that the criterion of efficiency of applying of curative solutions in improvement of the aquifer's water level with the weight of 0.311 was the most important one. Three multi-criteria decision making methods namely, Simple Additive Weighting (SAW), Technique for Order Performance by Similarity (TOPSIS), and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR) were utilized to select the best curative solution. The solution of 10% reduction of pumping rate and the construction of Gelvard dam in the SAW and TOPSIS methods and the solution of 3% reduction of pumping rate and the construction of Gelvard dam in the VIKOR method ranked first. Combined techniques namely, the Rank Average Method, Borda's Method, and Copeland's Method were used to develop a consensus on prioritizing curative solutions for the Tajan Aquifer. The results of these techniques showed that the solution of 10% reduction in pumping rate along with the construction of the Gelvard dam was the best. The results of simulating this solution demonstrated a 1.91 m improvement in the groundwater level of the aquifer in the MODFLOW code and a 361.5-m recede in seawater intrusion length along the coast in the SEAWAT code. • Saltwater intrusion from the sea or saline lakes into freshwater aquifers degrades the potable quality of these resources. • Appling MODFLOW, MT3DMS, and SEAWAT to simulate groundwater flow, solute transport, and seawater intrusion. • Proposing 11 curative solutions to control seawater intrusion in Tajan aquifer located in Iran. • Using MCDM methods to select the best curative solutions. [ABSTRACT FROM AUTHOR]

Abstract: The selection of residence location in different countries is of high priority and significance for tourists. The selection of the most appropriate hotel entails a rather complicated decision-making process. A comprehensive hotel selection model can empower the hotel managers, the tourists, and the tourism industry to make decisions based on more effective indicators of high quality services for a higher rate of satisfaction. The purpose of this research is to deeply explore the broad literature and to identify the most significant hotel selection indicators and factors in Tehran hotels and to present a comprehensive model through an exploratory factor analysis of the extracted indicators so as to provide the managers and tourists with a firm ground for making better decisions regarding the indicators of hotel selection. Promenade and comfort, security and protection, network services, pleasure, staff and their services, news and recreational information, cleanliness and room comfort, expenditure, room facilities and car parking were identified as the main hotel selection factors of Tehran hotels. Afterwards, another factor analysis has been done in order to extract the next hidden set of factors within the aforementioned factors which return two main factors of “Hotel Comfort Factors” and “Hotel Compensatory Factors”. Following the creation of the final model and based on the intrinsic vagueness of decision making in the process of selection, a set of fuzzy membership functions for the extracted factors has been provided. The intention has been to provide the expert system and decision support system developers and users with a set of practical indicators in order to help them design and implement realistic systems based on the deeply studied indicators and factors of hotel selection. Such supportive systems can be directly presented to the tourists requesting a mechanism for selecting the most appropriate hotel but lacking enough information about the important indicators and factors and also to the managers of hotels who are trying to make strategic decisions regarding the most optimized investments on the indicators of selecting a hotel. Considering the priorities of tourists, hotel managers, entrepreneurs and investors in the hotel industry require deep investigations and studies for which this paper provides a firm basis. [Copyright &y& Elsevier]

Abstract: Previous studies have shown that a well-known multi-criteria decision making (MCDM) technique called Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE II) to explore porphyry copper deposits can prioritize the ground-based exploratory evidential layers effectively. In this paper, the PROMETHEE II method is applied to airborne geophysical (potassium radiometry and magnetometry) data, geological layers (fault and host rock zones), and various extracted alteration layers from remote sensing images. The central Iranian volcanic-sedimentary belt is chosen for this study. A stable downward continuation method as an inverse problem in the Fourier domain using Tikhonov and edge-preserving regularizations is proposed to enhance magnetic data. Numerical analysis of synthetic models show that the reconstructed magnetic data at the ground surface exhibits significant enhancement compared to the airborne data. The reduced-to-pole (RTP) and the analytic signal filters are applied to the magnetic data to show better maps of the magnetic anomalies. Four remote sensing evidential layers including argillic, phyllic, propylitic and hydroxyl alterations are extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images in order to map the altered areas associated with porphyry copper deposits. Principal component analysis (PCA) based on six Enhanced Thematic Mapper Plus (ETM+) images is implemented to map iron oxide layer. The final mineral prospectivity map based on desired geo-data set indicates adequately matching of high potential zones with previous working mines and copper deposits. [Copyright &y& Elsevier]

Abstract: Many developing countries strive to cover their need for cement by domestic productions. The rising number of cement factories in these countries gives evidence to this. However, the ambition comes along with considerable environmental impacts that can be attributed to this industry. Policy makers, manufacturers and the public are becoming more and more aware about the environmental issues attributed to cement production. Striving for an environmental friendly production of this good is an urgent need. This paper discusses how environmental evaluation of the cement industry in Iran can be facilitated. Up to now, there is no standard or coherent method available to proceed with the evaluation. To advance environmental evaluation, a set of appropriate indicators have been developed by cooperating with experts from university, industry and policy makers. Five representative cement factories in Iran were then surveyed to derive quantitative data for the indicators. This helped to picture the current performance of this industry sector. The importance of the indicators was determined with the help of the cooperating industrial partners. By using the TOPSIS method, indicators were prioritized and improvement strategies for this industrial sector were derived. 15 indicators are introduced; among them seven are for the intensity of consumptions during production of cement and emissions production, three for control of emissions to air, four for capacities of control of water pollution and one for the inefficiency level in the execution of ISO 14000. It shows that the last indicator has the highest priority followed by the intensity of CO2 emission. [Copyright &y& Elsevier]

Abstract: This paper describes the application of a well-known Multi Criteria Decision Making (MCDM) technique called Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE II) to explore porphyry copper deposits. Various raster-based evidential layers involving geological, geophysical, and geochemical geo-datasets are integrated to prepare a mineral prospectivity mapping (MPM). In a case study, thirteen layers of the Now Chun copper deposit located in the Kerman province of Iran are used to explore the region of interest. The PROMETHEE II technique is applied to produce the desired MPM, and the outputs are validated using twenty-one boreholes that have been classified into five classes. This proposed method shows a high performance when providing the MPM while reducing the cost of exploratory drilling in the study area. [Copyright &y& Elsevier]

Abstract: Landfill site selection is a complicated multi criteria land use planning that should convince all related stakeholders with different insights. This paper addresses an integrating approach for landfill siting based on conflicting opinions among environmental, economical and socio-cultural expertise. In order to gain optimized siting decision, the issue was investigated in different viewpoints. At first step based on opinion sampling and questionnaire results of 35 experts familiar with local situations, the national environmental legislations and international practices, 13 constraints and 15 factors were built in hierarchical structure. Factors divided into three environmental, economical and socio-cultural groups. In the next step, the GIS-database was developed based on the designated criteria. In the third stage, the criteria standardization and criteria weighting were accomplished. The relative importance weights of criteria and subcriteria were estimated, respectively, using analytical hierarchy process and rank ordering methods based on different experts opinions. Thereafter, by using simple additive weighting method, the suitability maps for landfill siting in Marvdasht, Iran, was evaluated in environmental, economical and socio-cultural visions. The importance of each group of criteria in its own vision was assigned to be higher than two other groups. In the fourth stage, the final suitability map was obtained after crossing three resulted maps in different visions and reported in five suitability classes for landfill construction. This map indicated that almost 1224ha of the study area can be considered as best suitable class for landfill siting considering all visions. In the last stage, a comprehensive field visit was performed to verify the selected site obtained from the proposed model. This field inspection has confirmed the proposed integrating approach for the landfill siting. [Copyright &y& Elsevier]

The purpose of this paper is to streamline the supply of corn, one of the key ingredients in the production of bioethanol. Using a comprehensive sustainable framework of criteria (including social, economic, and environmental dimensions), the potential locations of corn cultivation in Iran are examined from a multi-criteria decision analysis perspective. To this end, we need to find the importance of the relevant evaluation criteria and a ranking method to rank the potential locations. Best worst method (BWM) is used to determine the weight of the criteria presented in the framework based on the opinion of a sample of Iranian experts, after which the 'preference ranking organization method for enrichment evaluations II' (PROMETHEE II) is applied to ranking the different provinces of Iran. To improve the ranking results, we extend the PROMETHEE II by employing a set of piecewise linear value functions, for which the performance of alternatives with respect to the criteria calculated by the piecewise linear value functions is used to determine the amount of deviation in the first step of PROMETHEE II. The results of the hybrid methodology indicate that the presence of water, land cost and air pollution are the most important factors determining the ranking of the alternatives, and that Kordestan is the best province for corn cultivation in Iran. • A sustainable framework is used for the location of biomass cultivation areas. • The weight of criteria in the framework are calculated using the best-worst method. • An extended PROMETHEEII is proposed for ranking the alternatives. • The proposed methodology is used to determine the corn cultivation areas in Iran. • Results indicate that Kordestan is first place for corn cultivation area in Iran. [ABSTRACT FROM AUTHOR]

Abstract: In recent years, numerous attempts have been made to reduce the global environmental and associated socio-economic impacts of construction activities to achieve sustainable development goals. A sustainable system or activity refers to an eco-friendly, cost effective and socio-politically viable solution. This paper utilizes triple-bottom-line (TBL) sustainability criteria for the selection of a sustainable flooring system in Tehran (Iran). Three types of block joisted flooring systems – concrete, clay, and expanded polystyrene (EPS) blocks – have been investigated using life cycle analysis (LCA). Proposed approach provides a comprehensive evaluation system based on TBL criteria that are further divided into thirteen sub-criteria. It includes: (1) Environmental concerns (resource depletion, waste and emissions, waste management, climate change, environmental risk, embodied energy and energy loss); (2) Economic concerns (material cost, construction cost, and occupation and maintenance cost); and (3) Socio-political issues (social acceptance, vulnerability of area, and building weight). Analytical hierarchy process (AHP) is used as a multi-criteria decision making technique that helps to aggregate the impacts of proposed (sub)criteria into a sustainability index (SI) through a five-level hierarchical structure. Integration of AHP and LCA provides a framework for robust decision making that is consistent with sustainable construction practices. A detailed analysis shows that the EPS block is the most sustainable solution for block joisted flooring system in Tehran. [ABSTRACT FROM AUTHOR]

Abstract: Geothermal exploration involves a high degree of uncertainty and financial risk, and requires reliable exploration data to constrain development decisions. The paper describes a geothermal exploration and resource identification method that is based on building a map of potential geothermal resource areas by combining geological, geochemical and geophysical datasets; it is a powerful tool for visualizing new and existing data during decision-making processes. By performing suitability analysis and geothermal area identification, and by establishing criteria to define geothermal resources with development potential, a map of Iran was constructed highlighting 18 promising areas. [Copyright &y& Elsevier]

Abstract: A large carbonate oil field in Iran is suffering from severe casing collapses. 48 casing collapses have been occurred due to reservoir compaction, poro-elastic effects and corrosion. The application of neural networks for predicting casing collapses using complex multi-dimensional field data has been undertaken. This paper shows how a neural network (ANN) system can be trained based on the parameters affecting casing collapse to estimate the potential of collapse of wells to be drilled as well as the current wells producing in the field. The potential use of this type of analysis is large in that it can be linked as a critical risking parameter in future field development analysis. Being able to quantify the potential for collapse of a well in the future can give management the foundation for a better financial decision making on what wells and where to drill them with the potential for the larger net return on the investment. The estimated collapse and corresponding depth could also benefit in the type of casing design and completion method to be selected as well as workover designs. Interpretation of the neural network results, together with engineering judgment, allowed us to conclude that using this method is technically feasible for predicting casing collapses in this field. [Copyright &y& Elsevier]

The purpose of this paper is to underscore the necessity for implementing a cleaner production strategy in order to achieve sustainable development for Iran''s industries. While reviewing the reasons for the need to adopt the strategy of cleaner production for the industries of developing countries, the special features of Iranian society which makes the use of cleaner production necessary were also studied.It is important to develop a model or method for developing a priority for industrialists to work with in initiating cleaner production activities. This was done in Iran using the “multiple criteria decision making method” (MCDM). This included, among other things, interviewing the relevant experts and directors, for each industrial group. A relative ranking score was developed and based upon it, the priority of each group was determined. Within this process, the industrial groups of “textiles, apparel and leather industries” were given the highest priority and the industrial group of “manufacture of wood and wood products, including furniture” were given the lowest priority. [Copyright &y& Elsevier]

Sustainable development programs rely on implementing energy policies in different sectors of a society. As far as agriculture sector is concerned, this paper intends to evaluate the current energy consumption and the potential for renewable energy programs' deployment in regional scale. The candidate region is Iran's Caspian Sea coastline. The assessment is modeled by recent multi-criteria decision analysis approaches, i.e. Level Based Weight Assessment (LBWA) with Weighted Aggregated Sum Product Assessment (WASPAS). The proposed index was designed so as to cover conventional and non-conventional energy resources subjects simultaneously, for instance: (1) biomass production, and (2) natural gas and diesel fuel at state level. From methodology point of view, the traditional WASPAS method is enhanced by the integration of the Weighted Power Heronian (WPHA) and Weight Geometric Power Heronian (WGPHA) functions. Application of these functions enables the elimination of the influence of extreme and unreasonable arguments in initial decision-making matrix. In addition, the interrelations between attributes is considered in the proposed model, that is particualrely appropriate for decision making in dynamic systems. The model capability in decision making has been investigated by comprehensive sensitivity analysis that implies in Iran's Caspian Sea coastline, Mazandaran state ranks first, followed by Guilan and Golestan. The result is suitable for policy makers and regional managers to define proper plans and actions in sustainable development of Caspian Sea coastline based on both agriculture-based energy efficiency as well as bio-based energy potential. [ABSTRACT FROM AUTHOR]

• We propose a novel multi-criteria data envelopment analysis model. • The proposed two-stage DEA is first considered in the presence of ratio data. • Three states are considered (black-box, free-link, and fix-link). • A multi-criteria structure is used to demonstrate the validity of the models proposed. • An illustrative example on the efficiency of 60 sets of bank branches in Iran is provided. Data Envelopment Analysis (DEA) is a well-known technique for assessing efficiency levels of decision-making units (DMUs). Very often, available data may be expressed as ratios and, in such cases, traditional DEA models cannot be applied as long as biased efficiency results are produced, yielding the issues of efficiency underestimation and pseudo-inefficiency. In this paper, a novel two-stage MCDEA-R model to handle ratio data is developed observing three distinct assumptions – black-box, free-link, and fixed-link – offering a multi-criteria decision making (MCDM) perspective to the efficiency assessment problem in productive networks. While the proposed models are tested by evaluating the efficiency levels of a set of 30 bank branches in Iran, their distinctive features are highlighted in terms of previous literature to model ratio data under network structures. Precisely, there were not only gains in terms of mitigating pseudo-inefficiency and lack of discrimination power of weights issues, but there were also actual gains in terms of efficiency reliability as measured by information entropy. [ABSTRACT FROM AUTHOR]

This research focusses on the selection of oil projects by using Multi-Attribute Decision Making (MADM) methods in an uncertain environment. Oil production plays a crucial role in the economy of Iran, a country with many opportunities for onshore oil exploration. Differently from other countries, however, oil producers in Iran face some constraints with respect to oil extraction because some areas are shared with other producers. Additionally, oil producers in Iran must also allocate scarce physical, human, and monetary resources among different projects. Inaccurate decision-making may not only yield sub-optimal revenue generation, but also adversely affect the national economy For these reasons, priority oil projects must observe a sequence of steps. In the first step, critical factors for selecting oil projects are collected from previous related studies and experts are interviewed. These factors are subsequently filtered using the Delphi method. The oil projects are then ranked using a comprehensive approach involving novel alternative MADM methods. The best-worst method (BWM) is a new MADM stream that relies on pairwise comparison. It presents several distinct advantages with respect to fewer computational steps and higher discriminatory power among alternatives. Differently from previous research, this paper couples BWM with Weighted Aggregated Sum–Product Assessment (WASPAS) to improve result sensitivity under uncertain decision-making environments as modelled by Z-numbers. A robustness cross-check against other MADM models is also presented. Results indicate that quality has the highest priority and that production technology has the lowest priority among ten factors for oil project selection, thus reflecting the impact of US sanctions on oil production in Iran. Managerial implications and future avenues of research are derived. • This research focusses on the selection of oil projects fields in Iran. • A novel hybrid MADM method in an uncertain environment is proposed. • BWM is coupled here with WASPAS and both are adjusted to handle Z-numbers. • Results indicate that quality has the highest priority and technology, the lowest. • Managerial implications and future research venues are derived. [ABSTRACT FROM AUTHOR]

This paper introduces the best–worst method to solve multi-attribute decision-making (MADM) problems in the fuzzy environment. In the proposed method, there is no need to do all the possible pairwise comparisons. In other words, only reference comparisons should be done. Reference comparisons consist of assessing the relative fuzzy preference of the best criterion (alternative) over others and all the criteria (alternatives) over the worst one. Afterward, a fully fuzzy linear mathematical model will be formulated and solved to determine the weight of the criteria. The same action will be performed to find the score of alternatives. This method has some interesting and valuable characteristics: (a) less required data for pairwise comparison, (b) high ability to provide a reliable solution, (c) it is an autonomous method along with its high capability to accompany another method. To evaluate the performance, it is compared with another fuzzy MADM method in an example. Furthermore, we apply this method for the maintenance evaluation of hospitals in Bojnord. The computational study confirms the high efficiency and satisfactory performance of the method, and results are validated by a low consistency ratio. Furthermore, the suggested methodology outperforms fuzzy AHP and well verified in the test instance. • Introduced a fully fuzzy best–worst method with a linear mathematical model. • Improved consistency ratio of fuzzy analytic hierarchy process. • Relevant example of office manager selection has been introduced. • Studied maintenance assessment in the hospitals of a city in the northeast of Iran. [ABSTRACT FROM AUTHOR]

The pathway of a modelling project is commonly described as an adaptively adjusted chain of steps at which various decisions are made. Communication and documentation about these decisions are crucial to enabling reflection and adapting the pathway to changing circumstances, such that well-informed planning is required. Project decision making, however, often remains a black box; it is rare to find reporting of dead ends, alternative decisions, and changes in decisions during the project. This paper uses an integrated environmental management case study in Iran to demonstrate the importance of reflective documentation and communication within the pathway. We show how a pathway diagram, incorporating some 14 symbols depicting steps, decision forks, options (selected and alternatives), actions, communication and documentation, can illustrate the role of communication within the project and identify lessons learnt. We also encourage further work on application of agile project management and social science techniques to improve modelling practices. Image 1 • Reflective communication helps to expose the black box of the modelling process. • Reflective documentation and communication within projects should be planned in advance. • Use of a pathway diagram illustrates the role of communication, identifies lessons learnt. • Effective communication along the project pathway is essential to adaptation. [ABSTRACT FROM AUTHOR]

• A practical framework towards RWH suitability assessment is presented. • A comprehensive, and comparative investigation of RWH in Iran at basin scale. • Theoretical, socio-economic and practical aspects of RWH systems were considered. • The implication of RWH systems on water crisis alleviation in MPB was discussed. Rainwater Harvesting (RWH) is becoming one of the most promising alternative sources of fresh water which can be potentially captured and utilized, particularly in arid and semi-arid regions (ASARs). However, identification of potential sites for RWH on a large scale has always been a great challenge, and therefore, requires further studies. Most recent studies on this topic select RWH zones employing Geographic Information Systems (GIS), combined with multi-criteria analysis and hydrological models. Nevertheless, there are a few studies, mostly in small catchments, that locate potential zones considering socio-economic factors. In this paper, a GIS-based Multi-Criteria Decision Analysis (MCDA) is presented to identify potential RWH areas incorporating socio-economic factors including distance from drainage networks, roads, urban areas, faults, farms and wells. The proposed methodology was implemented at a large catchment scale in Mashhad Plain Basin with an area of 9762 (km2) located in the northeast of Iran. Results show that 48% of the study area is not suitable for RWH. The rest of the study area is divided into three potential zones that are poor, moderate and good for RWH, covering 31%, 43%, and 26% of the potential areas, respectively. Ponds and pans, check dams and terracing were considered as the best practices for the good RWH potential areas. Preliminary estimates suggest that up to 158, 135 and 110 M m3 of precipitation could be received respectively by each system. [ABSTRACT FROM AUTHOR]

• Developing DEA-based road safety model based on decision makers' preferences. • Introducing a novel group BWM for considering DMs' judgments, simultaneously. • Estimating Final road safety efficiencies based on group BWM-DEA-RS model. • Investigating road safety performance of provinces in Iran. Evaluating road safety is an important issue for policy makers. One of the most important model for evaluation of road safety is data envelopment analysis-based road safety (DEA-RS). Conventional DEA-RS model is unable to consider decision makers' (DMs) judgements in the evaluations and also suffers from weight flexibility of input and output variables. In this paper, to incorporate DMs' preferences into decision making process and overcome the weight flexibility shortcoming of DEA-RS model, DEA-RS is combined with group best-worst method (BWM). For considering the preferences, a group BWM is proposed. The proposed model is applied to estimate the road safety efficiency in provinces of Iran. The results show that developed provinces such as Tehran has the safest roads in Iran. In contrast, provinces with poor road facilities are unsafe provinces in roads. At last, to improve the road safety performances, managerial implications and recommendations have been made for policy makers. [ABSTRACT FROM AUTHOR]