In this study, the performance of the algorithms of whale, Differential evolutionary, crow search, and Gray Wolf optimization were evaluated to operate the Golestan Dam reservoir with the objective function of meeting downstream water needs. Also, after defining the objective function and its constraints, the convergence degree of the algorithms was compared with each other and with the absolute optimal values obtained from GAMS nonlinear programming method (19.41). These values together with each algorithm optimization results were ranked using six Multi-Criteria Decision-Making methods of TOPSIS, VICOR, Linmap, Codas, ELECTRE and Simple Additive Weighting after obtaining the performance evaluation criteria of each algorithm (Reliability, reversibility, and vulnerability). Finally, integration methods (Mean, Borda, and Copland techniques) were used to evaluate the performance of Decision models. The results showed that the mean responses of the gray wolf, the whale, differential evolutionary, and crow search algorithms were 1.08, 1.49, 1.29 and 1.19 times the absolute optimal response and the answers’ coefficient of variation obtained by Gray Wolf algorithm was 113.2, and 1.43 times smaller than the whale, differential evolutionary, and crow search algorithms, respectively. Moreover, all integration techniques indicated the superiority of the gray wolf algorithm. Then, the Crow search, Differential evolutionary, and whale algorithms were ranked second to fourth, respectively. On the other hand, the use of these methods in solving the problem of Golestan Dam reservoir optimization was considered appropriate due to the similarity of the results obtained from the integration techniques with the results of TOPSIS, VICOR and Linmap methods.

The purpose of this study is to explain the ability of the simulation methodology to consider uncertainty of the multi criteria Decisions Making. The rank order of Decision alternatives depends on two types of uncertainty: (1) uncertainty associated with the Decision Making judgment regarding each element of Decision matrix described by distribution function, and (2) uncertainty regarding the future characteristics of the Decision Making environment described by a set of scenarios. Scenario is description of the Decision Making environment into some separate situations. Researchers concentrate on this type of uncertainty less than other types.Both types of uncertainty are capable to opposite the rank of alternatives and decline the certainty of Decision maker to the rank order of alternatives. In The present research, a simulation approach for handling both types of related uncertainty was described. The final conclusions showed that when uncertainty associated with the Decision Making judgment regarding each element of Decision matrix increases, the probability of rank reversion and rank uncertainty increases too. Under these situations, the final ranking of the alternatives is probabilistic.

Physical development of cities requires studying a wide range of information to achieve sustainable development. In this study, which has been examined the potential of northern of Karaj city for urban development, Multi Criteria Decision Making ((MCDM)) and Analytical Hierarchy Process (AHP) have been used to pairwise comparisons of biophysical, environmental and social-economic criteria. Results have shown, despite the fact that social-economic criteria have allocated minimum weight than biophysical and environmental criteria had a significant impact in limiting the area for development. Furthermore, the results that have given by sensitivity analysis graphs and final maps shown basin area north of Karaj, has a limited ability to develop the city with power potential. Area in the region that can be grade 1 (suitable) have been identified, the 18.38 percent of total basin areas to 1855.50 hectares are allocated.

Cryptocurrencies have grown as one of the significant technological advancements in today’s digital age. Investors all around the globe have shown a growing interest in cryptocurrencies in recent times because of their potential to bring huge profits. This paper tries to determine the best cryptocurrencies for investment by evaluating six leading cryptocurrencies, selected based on market capitalization and global relevance. Cryptocurrencies are ranked using six important evaluation criteria using two Multi-Criteria Decision-Making ((MCDM)) techniques: Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), employed under hyperbolic fuzzy set (HyFS) settings. In addition, a closeness coefficient is introduced in TOPSIS method to enhance Decision precision and sensitivity. Although the results obtained by the two methods are very close, investors would not want to have any doubt about the investment they are considering. The rankings from each procedure are then combined using a social choice function: the Borda Count method. Combining these approaches, the findings indicate that Bitcoin and Ethereum emerge as the most favorable cryptocurrencies for investment among the selected alternatives. To ensure the consistency of the obtained rankings, statistical analyses were conducted. Spearman’s rank correlation coefficient (ρ), Kendall’s tau (τ), and the Wilcoxon Signed-Rank Test were utilized to measure the degree of agreement between the rankings generated by Hyperbolic Fuzzy TOPSIS and Hyperbolic Fuzzy VIKOR. Combining these approaches to create a trustworthy Decision-Making model for cryptocurrency selection makes this work novel.

Identifying and locating suitable areas for eco-tourism development, is one of the important issues of tourism planners. But the wide variety of options and parameters, variables uncertainty and long terms in environmental planning, causes the Decision-Making becomes more complex. So Multi-Criteria Decision-Making methods can meet these challenges. Thus the aim of this study is to identify suitable areas for eco-tourism in Kiamaky wildlife refuge using (MCDM) method Based on fuzzy logic in GIS. According to the effective criteria on the eco-tourism in this area; obtained from previous research and expert opinions, 15 criteria maps (climate, lithology, height from sea level, slope, aspect, land use and distance maps from residential area, road, river, police station, environmental guard station, sensitive habitats, shrine, spring and waterfall) are produced and classified as input. To determine the weights of criteria, opinions of experts in the form of Delphi Method were applied. The criteria matrix formed and the relative importance of all criteria was defined using the AHP method and pairwise comparison. Finally eco-tourism appropriate priority map was produced using Weighted Linear Combination (WLC) method and applying the index of the importance of each criterion to corresponding classified map. According to mentioned map, 15% and 34% of the area eligible for perfect and good for eco-tourism respectively, and 4% of the area are medium for this purpose. In this study, besides confirming previous studies, power and usefulness of GIS in locating and combining different ecological criteria were shown.