In terms of competitors, spectators, and media interest, cricket is one of the favorite international sports. At the international level, cricket may be played in three formats: a five-day Test, a one-day International (ODI) for each squad of 50 overs, and a Twenty-Twenty (T20) for each team of 20 overs. Various online games that are based on the aforementioned cricket forms allow players to form a virtual squad of real-life players and score points based on how well they perform in real matches. A user gains better rank on the leaderboard if they get the most points in all of the contests they have participated in. Dream11 is one such online gaming platform which offers free and paid contests and thereby gamers can win some cash rewards. So users can select the eleven players and form a team. These eleven players should be selected from the two teams between which the match will be played. Additionally, these eleven players may be chosen from either one team or a combination of the two teams. To identify the eleven players for the T20 cricket format who can provide the maximum score to get the best rank in competitions, many studies employ Multi Criteria Decision Making (MCDM).In this paper, the TOPSIS method is utilized (weights of the performance factors of players are evaluated by using AHP) to determine the top eleven players.

In this paper we develop a fuzzy TOPSIS method based on intuitionistic fuzzy values to solve multiple criteria decision making problems in which the performance rating of alternatives values and the weights of criteria are given by linguistic terms. Arithmetic operations between intuition-istic fuzzy values are used for normalizing imprecise ratings and weights of criteria. In order to demonstrate the effectiveness of the suggested method, we propose a case study aiming to evalu-ate and compare the service quality of five major airports in North Africa. The suggested method helps manager of airports know the needs of passengers and the priority of enhancing service items.

Evaluation of faculty members is very significant for educational organization to prompt reputation of the organization and to provide quality education. Teaching staff, the pillars of the educational institution, can change the whole nation stimulating the magnet of interest, knowledge, and wisdom in the pupils. Selecting a better academic staff among the others is very crucial for Human Resources Management (HRM) as the success of any organization solely depends on how well it selects its manpower. Institute managing committee must have a reliable technique to judge a teachers’ ranking through multiple conflicting criteria because different teachers have various capabilities. In Bangladesh, it is a common practice in public engineering universities to select teachers only having good academic records. But teaching staff selection problem is a multi-staged decision-making problem having both quantitative and qualitative criteria. It is evident that it has become challenging as the number of alternatives and conflicting criteria increases. In this paper, a structured framework has been developed using MCDM methods both in fuzzy as well as non-fuzzy environments in the renowned engineering university of Bangladesh, where seven candidates under fifteen different sub-criteria are evaluated and ranked. The study helps the recruitment panel of educational organization in Bangladesh select the most eligible academic staff for required posts.

Suitable project manager has a significant impact on successful accomplishment of the project. Managers should possess such skills in order to effectively cope with the competition. In this respect, selecting managers based on their skills can lead to a competitive advantage towards the achievement of organizational goals. selection of the suitable project manager can be viewed as a multi-criteria decision making (MCDM) problem and an extensive evaluation of criteria, such as Technical skills, experience skills, Personal qualities and the related criteria must be considered in the selection process of project manager. The fuzzy set theory and MCDM methods appears as an essential tools to provide a decision framework that incorporates imprecise judgments and multi criteria nature of project manager selection process inherent in this process. This paper proposes the joint use of the Fuzzy DEMATEL (FDEMATEL) and Fuzzy VIKOR methods for the decision-making process of selecting the most suitable managers for projects. First, with the opinions of the senior managers based on project management competency model (ICB-IPMA), all the criteria required for the selection are gathered. Then the FDEMATEL method is used to prioritize the importance of various criteria and FVIKOR used to rank the alternatives in a preferred order to select the best project managers from a number of alternatives. Next, a real case study used to illustrate the process of the proposed method. Finally, some conclusions are discussed at the end of this study.

Component-based software system (CBSS) development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.

Strategic warehouse location-allocation problem is a multi-staged decision-making problem having both numerical and qualitative criteria. In order to survive in the global business scenario by improving supply chain performance, companies must examine the cross-functional drivers in the optimization of logistic systems. A meticulous observation makes evident that strategy warehouse location selection has become challenging as the number of alternatives and conflicting criteria increases. The issue becomes particularly problematic when the conventional concept has been applied in dealing with the imprecise nature of the linguistic assessment. The qualitative decisions for selection process are often complicated by the fact that often it is imprecise for the decision makers. Such problem must be overcome with defined efforts. Fuzzy multi-criteria decision making methods have been used in this research as aids in making location-allocation decisions. The anticipated methods in this research consist of two steps at its core. In the first step, the criteria of the existing problem are inspected and identified and then the weights of the sector and subsector are determined that have come to light by using Fuzzy AHP. In the second step, eligible alternatives are ranked by using TOPSIS and Fuzzy TOPSIS comparatively. A demonstration of the application of these methodologies in a real life problem is presented.

Today, the world facing with huge flood of data and the recent advances in computer technology have provided the capability to process significant amount of data. On the other hand, analyzing the information requires resources that most institutions do not have, independently. To handle such circumstances, grid computing has emerged as an important research area where the calculation of distributed computing and clustering are different. In this study, we propose a grid computing architecture as a set of protocols that use the cumulative knowledge of computers, networks, databases and scientific instruments based on the implementation of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique. The results of the implementation of the proposed algorithm on grid systems indicate the superiority of the proposed approach in terms of validation criteria scheduling algorithms, such as task completion time and the performance compared with some alternative method.

The present paper is aimed at multi-objective scheduling in an agent based holonic manufacturing system to satisfy the goal of several communities namely the product, the resource, and the organization simultaneously. In this attempt, first a multi criteria based priority rule is developed following Simple Additive Weight (SAW) method under Multi Criteria Decision Making (MCDM) environment to rank the products. Accordingly, the products are allowed to select a particular resource for execution by negotiation considering minimum time as criterion. The interests of different communities are accomplished by allocating the ordered rank of products to the ordered rank of resources. Conflict, if arises between products and resources, are resolved by introducing the concept of Early Finish Time (EFT) as criterion for task allocation. A scheduling algorithm is proposed for execution of the rule. In view of machine failure, a cooperation strategy is evolved that also optimizes reallocation of the incomplete task. It is concluded that the proposed scheduling algorithm together with the disturbance handling algorithm are poised to satisfy the agent’s local objective as well as organization’s global objective concurrently and are commensurable with multi agent paradigm.

In today’s competitive economy, quality plays an essential role for the success business units and there are considerable efforts made to control and to improve quality characteristics in order to satisfy customers’ requirements. However, improving quality is normally involved with various criteria and we need to use Multi Criteria Decision Making (MCDM) to handle such cases. In this state-of the-art literature survey, 45 articles focused on solving quality problems by MCDM methods are investigated. These articles were published between 1994 and 2013.Seven areas were selected for categorization: (1) AHP, Fuzzy AHP, ANP and Fuzzy ANP, (2) DEMATEL and Fuzzy DEMATEL, (3) GRA, (4) Vikor and Fuzzy Vikor, (5) TOPSIS, Fuzzy TOPSIS and combination of TOPSIS and AHP, (6) Fuzzy and (7) Less frequent and hybrid procedures. According to our survey, Fuzzy based methods were the most popular technique with about 40% usage among procedures. Also AHP and ANP were almost 20% of functional methods. This survey ends with giving recommendation for future researches.