With the complexity and amount of information in a wide variety of comparative performance reports in poultry production, making a decision is difficult. This problem is overcomed only when all data can be put into a common unit. For this purpose, five different decision making analysis approaches including  Maximin, Equally likely, Weighted average, Ordered weighted averages and Technique for order preference by similarity to ideal solution were used to choose the best broiler strain among three ones based on their comparative performance and carcass characteristics. Commercial broiler strains of 6000 designated as R, A, and C (each strain 2000) were randomly allocated into three treatments of five replicates. In this study, all methods showed similar results except Maximin approach. Comparing different methods indicated that strain C with the highest world share market has the best performance followed by strains R and A.

Multicriteria decision analysis tool is used in many water resources and environmental management projects. The Malnichara is one of the natural channels in Sylhet city (Bangladesh) responsible for storm runoff conveyance to the downstream Surma river. The channel is found to be encroached at many locations of the city and found to be very vulnerable. The authority has taken decision to improve natural channels by a traditional approach, e.g. constructing box culvert. In most cases, stakeholders’ participation is ignored in such type of decision making. Hence, efforts were made to evaluate three common alternatives viz. sodding natural channel, lined natural channel and box culvert for the channel improvement. The channel is hydrologically divided into two parts: the upper portion (Choukidekhi-Kanishail) and the lower portion (Kanishail-Topoban). Both parts were separately analyzed. Small groups of stakeholders were interviewed for the selection of criteria and for the assignment of weighed factor and scores. Experts’ opinions were also taken through consultation. Nine criteria from four categories such as technical, economic, environment and social aspects were selected. The relative performances of alternatives were evaluated using the weighed sum technique of multicriteria decision analysis. It was found that the sodding natural channel is the best alternative for both portions of the channel. However, the choice is very sensitive to the social criteria.

Background and Objective: Inundation in urban areas due to dens storm has created many problems for all cities thorough the world. Urban flood hazard zoning may provide useful information for dealing with contingency and alleviating risk and loss of life and property. Therefore, in order to manage urban areas, take relief measures and prioritize areas to solve the problem of floods, the areas that are most affected should be identified. Method: Vulnerability of urban areas often includes multicriteria that are associated with flooding. One of the methods that are sufficiently accurate and available which can identify flood hazard zoning, is using multicriteria decision analysis (MCDA) that in this study was used to determine the potential of flood risk in urban area. Six variables include: distance to the main channel, slopes, land use, drainage density, slope of the main channel and elevation was used. After determining paired comparison matrix, layers weight was determined by using the knowledge of experts and experts in the region and finally the map of urban flood hazard were identified. Findings: Hazard Potential Map showed that 8. 2% of the areas near to the outlet and located around the main channel are at highest hazard potential. Discussion and Conclusion: The results and field investigation showed multicriteria decision analysis is accurate and appropriate method for urban flood hazard zoning and using this method can identify areas with a greater flooding risk.

Objective Analyzing customer feedback from airline websites is more effective than traditional questionnaire-based methods, as these websites provide highly accurate and comprehensive information. Using big data technology, these websites collect and analyze millions of passenger reviews, offering more accurate information about customer experiences. Online reviews, as an open platform, provide the opportunity for employers to receive criticisms and suggestions, and due to their high volume and widespread dissemination, they can serve as a valuable source for analyzing customer sentiments and needs. Therefore, this study aims to propose a data-driven framework for ranking airlines, combining multi-criteria decision Making (MCDM) methods with Sentiment analysis (SA) at the aspect level. The main objective of this research is to evaluate the quality of airline services and rank them based on the reviews recorded on the SKYTRAX website from the users' sentiments hidden in their reviews.   Methods The proposed framework consists of three stages: Stage (1): After collecting the data and preprocessing the text, airline features were extracted using the High Attribute Clustering (HAC) algorithm. Stage (2): Sentiment orientation in each airline was identified to calculate the performance scores for each airline. Stage (3): Airlines were ranked using the TOPSIS method based on intuitive fuzzy numbers, considering the scores obtained in the second stage. Intuitive Fuzzy Sets (IFS) were used to represent effective customer opinions, including hesitant phrases in the decision matrix. Also, the criteria weights were determined through the entropy method.   Results The performance of 10 airlines was analyzed, and ranked accordingly. The results show that for economy class airlines, with a weight of 0.17, features such as customer service, legroom, flight delays, and security inspection, each with a weight of 0.11, are equally important to passengers as other features. According to the results, Middle East Airlines demonstrates the highest performance among the ten airlines (Saudi Arabian Airlines, Kuwait Airways, Oman Air, Iran Air, Egyptair, Royal Jordanian Airlines, Middle East Airlines, Pegasus Airlines, flydubai, and Air Arabia) i.e. it has the closest distance to the positive ideal solution of the fuzzy intuitive set and the farthest distance from the negative ideal solution of the fuzzy intuitive set. While Pegasus Airlines has the closest distance to the negative ideal solution and the farthest distance from the positive ideal solution, its performance is the lowest among the four airlines.   Conclusion This research greatly assists Middle Eastern airlines in seeking areas for improvement and in comparing their performance with their competitors to achieve a better competitive advantage in the market. The data from this research can be used to create a recommendation system for travelers helping them choose airlines that best align with their expectations, preferences, and travel goals. This can take into account factors such as budget, destination, and flight class, which can help airline managers better understand and meet customer needs.

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.