In the field of logistics, there is a daily need for decision making, i.e. the need to solve business problems by selecting an appropriate solution. During the implementation of decision-making processes, it is necessary to find an optimal solution that will best meet the needs of companies. The selection of an optimal solution is crucial for the profitability, cost-effectiveness and long-term development of companies. The decision-making process in logistics is facilitated by applying various tools such as multi-criteria decision-making methods. In this paper, an integrated SWARA (Step-wise Weight Assessment Ratio Analysis) – MARCOS (Measurement Alternatives and Ranking according to Compromise Solution) model was developed and applied in order to classify products. Fifty alternatives, i.e. products were evaluated based on three criteria. The first criterion is the quantity of purchased products, the second criterion is the unit price of products and the third criterion is the annual value of purchase. The SWARA method was applied to determine the significance of the criteria, while the classification of products was performed using the MARCOS method. According to the results of the originally created MCDM model, the products were grouped into three categories A, B, and C. Then, a sensitivity analysis was performed using a model involving the integration of SWARA method and ABC analysis. Using this model, the classification of products into three groups was performed on the basis of the aforementioned criteria, and then a comparative analysis was conducted.

Aim Urban furniture is one of the components influencing the appearance of cities, which plays an active role in the functional and aesthetic dynamics of cities. The current research was conducted with the aim of comparative analysis of urban furniture indexes. Methodology Using MARCOS technique, the indicators related to urban furniture and urban beautification in Isfahan metropolis have been analyzed. The research Method was Quantitative and its data is adapted from the statistics of Isfahan metropolis in 2019. Using Shannon entropy model, the weight of urban furniture indices has been calculated and these weights have been used in MARCOS technique. Using the final score of F (K) of MARCOS technique, analyze the indicators studied in Isfahan metropolitan. Findings The value of Si coefficient for anti ideal (0. 151) was obtained and the highest value of this coefficient belonged to region 1 (0. 6794). The highest value of K-coefficient (505. 4) and the highest value of K + coefficient (0. 679) have been obtained, which belongs to region 1 of Isfahan metropolis. The lowest value of these coefficients belonged to 13 Region of Isfahan. Using MARCOS technique, the final score of F (K) for Region 1 (0. 666), Region 2 (0. 283), Region 3 (0. 648), Region 4 (0. 473), Region 5 (0. 503) Region 6 (0. 649), Region 7 (0. 488), Region 8 (0. 465), Region 9 (0. 387), Region 10 (0. 482), Region 11 (0. 397), Region 12 (0. 524), region 13 (0. 268), region 14 (0. 325) and region 15 (0. 328) have been obtained. Conclusion The final score of MARCOS technique for urban furniture indicators in 15 Regions of Isfahan metropolis indicates inequality in the studied indicators.

MARCOS Novak mainly considers a type of architecture cuts loose from the expectations of logic, perspective, and laws of gravity, and has invented a set of conceptual tools for thinking about and constructing territories in cyberspace. Novak introduces the concept of "liquid architecture” , a fl uid, imaginary landscape that exists only in the Digital domain. He views trans-architecture as an expression of the "fourth dimension” , which incorporates the time alongside space among its primary elements. Novak's liquid architecture bends, rotates, and mutates in interaction with the person who inhabits it. In liquid architecture, "science and art, the worldly and the spiritual, the contingent and the permanent, " converge in a poetics of space made possible by emerging, virtual reality technologies. Novak describes his work as a process of metamorphosis, a “ symphony of space” , in which 3D constructions have the properties of Music, an experience he has since referred to as “ Navigable Music” . In this paper what considered are those phenomenological and post structural approaches and states that they also have become outdated. New senses have been attained through the crossbreeding between the reality of the individual and the virtuality of the structure. A strong concept of space, then comes forward, where the manifestation of mind in the realm of the body calls for what is to be perceived as real. The architecture is now characterized by the fusion of information, art, and technology; the purpose of this research, to question how those realities are constructed and how they take the individual into account.

Dual probabilistic linguistic term sets (DPLTSs) are more powerful compare to probabilistic linguistic term sets, probabilistic hesitant fuzzy sets, hesitant fuzzy sets and intuitionistic fuzzy sets for the reason that they deal with both belongingness grades and non-belongingness grades along with their respective probabilities. On the other hand, the generalized Dombi operators have higher flexibility due to inclusion of two parameters. MARCOS (Measurements alternatives and ranking according to compromise solution) technique was developed by utilizing the utility degrees of options using the ideal and anti-ideal solutions. Here, we combine the merits of generalized Dombi operator and MARCOS and propose a DPL-MARCOS approach under dual probabilistic linguistic setting. In this methodology, the concepts of consistency and similarity between the experts are used to calculate their weights of subjective and objective types, respectively. For aggregating experts' preferences, we propose dual probabilistic linguistic- generalized Dombi weighted averaging aggregation operator. A biomass feedstock selection problem is furnished to show the applicability of our technique. We have considered coconut shell, coffee husk and sugarcane baggage as alternatives. The result shows that coffee husk is the most suitable option. The sensitivity assessment of parameter values reveals that our technique is stable. The comparative study proves that our model is more significant and realistic compare to the existing ones.

One of the most important things to do when deciding on projects is to choose the right contractor. Choosing inappropriate contractors causes problems such as high delays, high costs, and poor quality of project execution. The evaluation and ranking of contractors is one of the important decisions and is one of the fundamental challenges in construction projects due to the existence of various criteria; the aim of this research is to rank contractors of Zahedan gas company using the MARCOS and Copperas model. Literature and research background, interviews with experts and experts were also used to identify and determine effective criteria of the Delphi method. The 7 main criteria categories included: financial resources, executive and equipment capacity, technical and planning capacity, experience, good track record, key staff and were identified to a specialized certificate. The Shannon entropy method has been used to determine the weight of the criteria. The criteria for experience, technical capacity and planning and key employees with weights of 0.17432, 0.17136 and 0.16879 are ranked first and third respectively, with the highest weight and most important criteria for selecting contractors. The results showed that the ranking in the MARCOS model has the best ranking option, the optimal performance of which is the most. Thus, the Fourteenth contractor ranked first with a value of 0.8931 and the fifteenth contractor ranked second with values of 0.8667 were also selected as the top contractors. Comparing the results of MARCOS and Copras showed that both methods correspond to each other, which can also be assured of the results of the MARCOS model.The possibility of considering a set of criteria while maintaining the sustainability of the method is one of the advantages of the MARCOS model. Therefore, it can be used in an efficient way with simple and accurate calculations for ranking.

Among the risks facing the plains in Iran is subsidence, which causes many problems in agricultural lands, roads, power, and energy transmission lines. In recent years, Sarab plain has faced a sharp drop in the level of underground water, which has caused this area to be exposed to the risk of subsidence. Therefore, the purpose of this research is to investigate and analyze the most important factors involved in creating the risk of subsidence in Sarab plain and to identify the susceptible surfaces that are likely to be involved in subsidence in the future, using the multi-criteria MARCOS and CODAS algorithms. According to the results of subsidence risk zoning, water depth, land use, and slope, respectively, with weight coefficients of 0.194, 0.171, and 0.159, are the most important factors involved in creating the risk of subsidence in the studied area. The output of the MARCOS method showed that, respectively, 167.50 and 276.09 square kilometers of the area of Sarab Plain, and results of applying the CODAS method, showed that 187.13 and 279.03 square kilometers of the area are in the high-risk and critical category. In addition, the map extracted from the MARCOS and CODAS algorithms with the depth of the water level of the wells, respectively, have correlation coefficient values of 0.77 and 0.81. A correlation can be seen between the output of both methods with the water level map. It seems that the results of this study can be of great help to organizational managers and land and soil resource planners for protecting and managing water resources and natural hazards and preventing land degradation.

Considering the climatic similarity of Iran's three northern provinces compared to the Netherlands, why does Iran have a low level of development in the agricultural sector? Can the Netherlands development model be used for the development of Iran's agricultural sector? The purpose of this research is to determine the level of development of the agricultural sector in the three northern provinces of Iran (Guilan, Mazandaran and Golestan) compare to the Netherlands. To achieve this goal, the MARCOS approach was used. The most important reason for using this method is more confidence and accuracy in solving multi-criteria decision problems. A method based on hierarchy and knowledge of conditions and limitations to solve business problems in the real world. The required statistics and information are obtained from agricultural statistics and databases such as the World Bank, the World Food and Agriculture Organization. The final results show the low level of development of Iran's three northern provinces compared to the Netherlands.this backwardness can be seen in: agriculture, horticulture, animal husbandry, mechanization, education and infrastructure sector. One of the most important reasons for the Netherlands success of is to use of advanced technologies and advanced greenhouses, including hydroponic agriculture, geothermal energy, artificial lighting technology, and hydroponics and aeronautics solutions. Therefore, Supporting the introduction of new technologies in the country can speed up the development of agricultural sector in Iran.

Aim&Background: with increasing the unreliability in the competitive and dynamic environment of the market, caring the supply chain resilience is important. whose start point is selection of resilient suppliers. Steel makers as one of the most important and vital industries of the country due to market disturbance and increase of currency price have have encountered raw materials supply problem specially iron ore supply. The aim of this research is to identify criteria of the resilient suppliers in the steel industry of Chaharmahal and Bakhtiari and rank it. Method: This research is of applicative kind which has been done by qualitative and quantitative method. During the aimed sampling, 10 of the experts acquainted with the research has been selected. In the qualitative section, Criteria affect the resilient supplier selection using theme analysis and during interview with experts has been identified. Then in the quantitative section weight of criteria was calculated using hierarchical analysis and the ranking of the 3 raw material supplier companies has been done using new MARCOS multi-criterion decision making method. Findings: In the qualitative section six criteria including information technology, delivery, safety, enviromental and social issues, quality, flexibility and agility using theme analysis and during interview with experts has been identified. After criteria weights were determined agility has been identified as the most important criterion. Ranking of suppliers was done using MARCOS method and it is showed that the acquired results using MARCOS method is compatible with the results of VIKOR, TOPSIS, COPRAS, and QULAIFLEX methods. Also it was showed that MARCOS method is sensible to probable changes in decision making criteria importance and method stability in supplier selection at the various circumstances of suppliers has been showed. Conclusion: Criteria which is determined in this research is compatible with criteria which was determined in previous researches. Also MARCOS method is simple, effective and stable for ranking the suppliers at the dynamic circumstances.

Extended AbstractIntroductionThe city, as human life, plays a fundamental role in creating a feeling of satisfaction, and in fact, it shapes the lifestyle of a person and determines the quality of his life. It should be noted that the quality of housing is directly related to the quality of life and the social and economic development of different communities; in such a way that the accommodation of families in inappropriate housing has become the basis of social problems and anomalies, which in turn, unfavorable social conditions will cause negative economic effects for societies. Quality of life studies can identify problematic areas, causes of people's dissatisfaction, residents' priorities. In life, the influence of socio-demographic factors on the quality of life and to monitor and evaluate the effectiveness of policies and strategies in the field of quality of life. According to the above, the purpose of this research was to measure the quality of life in Urmia city and five regions based on housing indicators. The originality and innovation of the current research can be expressed in the application of the new BWM (2015) and MARCOS (2019) models as well as the combined physical, economic, social and demographic indicators.Materials & MethodsAccording to its purpose, this research is an applied research and according to the method of doing the work, it has a descriptive-analytical nature. The information was collected through library studies, field studies and census data of Iran Statistics Center in 2015. Thus, after studying the sources related to the research topic, 12 indicators have been selected to reach the research output, which include household density in a residential unit, population density in a residential unit, building age, building quality, building strength, land value, access to services. Education and treatment, housing ownership, plot area, infrastructure level, access to green space and residential density. Considering that each of the housing indicators used to model the quality of life has a different importance coefficient, therefore, in this article, the opinions of elites have been used to determine the weight of the indicators. In order to weight the indicators based on the BWM method, 10 questionnaires whose content is based on the pairwise comparison of indicators based on the preference of the best indicator over other indicators and the preference of other indicators over the worst indicator have been compiled. In the next step, the data of the questionnaires were entered into the GAMS software and were calculated and analyzed. The highest weight obtained is related to the building quality index with 0.201 and the lowest is related to the age of the building with an importance coefficient of 0.017. After calculating the weight of the indicators, in order to perform spatial analysis, first the information layers of the indicators were digitized and edited in the software of the geographic information system, and by converting the information layers into a raster and standardizing them based on the purpose of the research, the importance coefficient calculated from BWM in each of The indicators have been multiplied and the combination of the indicators has been discussed by applying weighting. In the last step, the MARCOS model was used to evaluate the quality of life in the five regions of Urmia.Results & DisscussionAfter the 12 indicators of housing to measure the quality of life in the geographic information system software were classified and analyzed using the reclassification command and based on the research objectives, in order to model the quality of life in the city of Urmia by using the summation command and applying the obtained weights Based on the best-worst method, the indicators have been combined. The results of the combination of 12 housing indicators to model the quality of life in Urmia show that 23% of the city is in the very low quality of life zone, 34% in the low quality of life zone, 13% in the medium quality of life zone, 20% in the The quality of life is high and 11% is in the area of ​​very high quality of life. Based on the output obtained from the Marcus model, in Urmia city, region one, region five, region two, region three and region four are ranked 1 to 5 in terms of quality of life based on housing indicators.ConclusionThe obtained results indicate that in general the quality of life in the eastern, northern, and northwestern parts of Urmia city is at an inappropriate level due to the presence of informal settlements, and the Shahrchai River border, which includes the 1st and 5th May areas. Due to the newly built area, it is in high quality. The results of the separate analysis of the indicators show that the quality of life in Urmia city based on the indicators of households in a residential unit, people in a residential unit, the strength of buildings, the area of ​​plots, access to educational and medical services and green space in a medium to high condition and based on the indicators The age of the building, the quality of the building, the value of the land, the level of infrastructure, housing ownership and residential density are in a medium to low condition.

Today, the crisis of the lack of vehicle parking areas, especially in central urban areas, has plagued most large cities, as the lack or shortage of public parking lots because of growing urban development has engendered increased traffic jams, pollution, reduced quality of life in cities, etc. The goal of this study was to employ the Marcus Model to examine 26 public parking lots in the central areas of District 1 of the metropolis of Ahvaz using seven indicators of area, facilities, access, security, beauty, entry fees, and cleanliness through survey methods. The statistical population of the study comprised public parking lot users of the city of Ahvaz. The sample volume was 111 using the KMO and Bartlett’s test. Cronbach’s alpha of 0. 861 was estimated for the reliability of the study questionnaire, which measures the accuracy and consistency of the findings. From an innovation perspective, the study aimed to broaden its focus on examining the indicators, as compared to previous research. This is because the effectiveness of each of the indicators under study varied in terms of capacity, place, thinking, user encounter, and officials’ monitoring. Also, one of the multi-criteria decision-making methods (MARCOS Model) was used to explain the study data. Study findings showed that out of the 26 public parking lots in the study area, story parking lots of Karun, Refah, Shaid Fahmide, Nakh, Shahed, etc. with the respective quantitative values of 91. 37, 89. 45, 87. 20, 86. 16, and 85. 74 ranking first to fifth in terms of the seven indicators examined.