Generation of solid waste is the integral consequence of civilization and its management is stand-ing as a big challenge in front of state government at present time. Municipal solid waste in Durg-Bhilai is littered with improper places due to lack of understanding about the scientific im-portance of garbage and its consequences. Our foremost concern is the selection of appropriate dumping area nearby Durg-Bhilai (C.G.) and for the selection of appropriate dumping area, a multi criteria decision making technique is used. This paper attempts to evaluate 4 dumping areas based on 5 criteria. Analytical hierarchy process (AHP) is used to determine the weighs for each criterion and quality function deployment (QFD) is also implemented. The results indicate that Potiyakala was the best dumping site nearby Durg-Bhilai area.

The ready-to-wear sector is expanding quickly and already accounts for a significant contribution to Ethiopia's export revenue. Due to its lower labor and investment costs, availability of resources, government assistance, etc. than other sectors, this industry attracts young entrepreneurs from around the nation as investment destinations. However, while investing in the leather industry, there are frequently many more aspects to consider. Again, there are numerous leather investment opportunities in the leathers sector, including handbags, jackets, belts, shoes, gloves, etc. Different sorts of leather items necessitate various levels of capital investment, operator skill sets, and resource requirements, among many other things. Again, based on their capacity for managing businesses, available capital, business location, and other factors, not all investors are in the same position. To assist investors in making decisions on the opening of a new leather industry, this paper presents a FAHP methodology for choosing the best leather item among various possibilities in a fuzzy environment. The methods enable the decision-maker to incorporate language expressions of expert judgment into the evaluation process. Using the suggested process, the ideal leather item is chosen for the launching of a leather industry in Ethiopia under the current circumstances.

A new flexible and adjustable model which is based on an Intuitionistic Fuzzy TOPSIS model with an exponential-related function and intuitionistic fuzzy entropy method has been presented and apply in this study. For supporting designers in determining design stakeholders’ preferences when finding the best compromise between new concepts design during early product develop-ment phase. The main advantage of the new model is that it is flexible and adjustable and affords the design stakeholders the option to a change of action in the event they receive new information or reason not to continue with a particular design or product. Finally, it uses both subjective and objective weights methods for the evaluation of the design concepts criteria, which makes the proposed model more realistic and more practical. The model has been applied for the design concept evaluation of seven forklift trucks with the view to improving the reliability of the machine.

Human resource management plays an essential role on development of any business organization. Selection of employee normally depends on various criteria such as employee commitment, necessary skills, etc. Therefore, a good strategy to hire appropriate employee is a multi-criteria decision making (MCDM) specially the ones, which could handle uncertainty, properly. In this paper, we present a method to use MCDM techniques for hiring employees. In fact, the present work proposes a Fuzzy Analytic Hierarchy Process (FAHP) as one of the most popular multi-criteria decision making techniques. A computer application is developed where it receives the configuration of the employee selection problem, evaluates the candidates and ranks them using the appropriate voting system.

Supplier evaluation and selection has been a vital issue of strategic importance for long time. Different multi-criteria decision making (MCDM) approaches have been proposed by the researchers in past, to solve the supplier evaluation and selection problem. In this paper, we present a review of various MCDM methodologies reported in the literature for solving the supplier evaluation and selection process. The review is solely based on sixty-eight research articles, including eight review articles in the academic literature from 2000 to 2011. We try to find out the most prevalent approach in the articles and thereby present the future scope of arriving at an optimal solution to the problem, based on the specifications, the strategies and the requirements of the buyers. The study presents that with the change in processes and the requirements, how the approach of the manufacturing industry has shifted from striving for operational effectiveness to the strategic partnership in the dyadic relationship.

One of the main challenges in Stock Market is to choose an appropriate combinations of various assets. The aim of this study is to propose a hybrid method, which is able to survey one problem with some criteria that it is very good for investment problem. In this study, we use a hybrid multiple criteria decision-making (MCDM) model, which shows the dependent relationships among criteria with DEMATEL method to build a relations-structure among criteria. We then use Analytical Network Process (ANP) to determine the relative weights of each criterion with dependence and feedback, and the VIKOR method is implemented to rank and select the best alternatives for investment. This study is in stock exchange in Iran to select the best stocks and the data are gathered through the years (2006-2010). There are a lot of methods to rank and select of firms that most of the methods just do one, ranking or selecting; but the used method in this study not only ranks the firms but also determines which firms (stocks) are best for investment, so that in this study 2 of 50 firms are proposed for investment.

Today global warming is on the rise and the natural resources are getting consumed at a faster rate. Power consumption has increased many folds to cater the human need. Thus renewable energy resources are the only option available at this juncture. Wind energy is one of the renewable energy. Location selection for wind farm takes an important role on power generation. However, the location selection is a complex multicriteria problem due to the criteria factors which are conflicting in nature as well as uncertain. The process becomes more complex when a group of decision makers are involved in decision making. In the present study, a COPRAS (COmplex PRoportional ASsessment) based multi-criteria decision-making (MCDM) methodology is done under fuzzy environment with the help of multiple decision makers. More specifically, this study is aimed to focus the applicability of COPRAS-F as a strategic decision making tools to handle the group decision-making problems.

In this paper, we examine advanced optimization approach for portfolio problem introduced by Black and Litterman to consider the shortcomings of Markowitz standard Mean-Variance optimization. Black and Litterman propose a new approach to estimate asset return. They present a way to incorporate the investor’s views into asset pricing process. Since the investor’s view about future asset return is always subjective and imprecise, we can represent it by using fuzzy numbers and the resulting model is multi-objective linear programming. Therefore, the proposed model is analyzed through fuzzy compromise programming approach using appropriate membership function. For this purpose, we introduce the fuzzy ideal solution concept based on investor preference and indifference relationships using canonical representation of proposed fuzzy numbers by means of their corresponding?-cuts. A real world numerical example is presented in which MSCI (Morgan Stanley Capital International Index) is chosen as the target index. The results are reported for a portfolio consisting of the six national indices. The performance of the proposed models is compared using several financial criteria.

One of the primary concerns on many countries is to determine different important factors affecting economic growth. In this paper, we study some factors such as unemployment rate, inflation ratio, population growth, average annual income, etc to cluster different countries. The proposed model of this paper uses analytical hierarchy process (AHP) to prioritize the criteria and then uses a K-mean technique to cluster 59 countries based on the ranked criteria into four groups. The first group includes countries with high standards such as Germany and Japan. In the second cluster, there are some developing countries with relatively good economic growth such as Saudi Arabia and Iran. The third cluster belongs to countries with faster rates of growth compared with the countries located in the second group such as China, India and Mexico. Finally, the fourth cluster includes countries with relatively very low rates of growth such as Jordan, Mali, Niger, etc.

During the past few decades, many organizations have attempted to increase their productivity
through outsourcing parts of their responsibilities. Outsourcing helps firms reduce their low
value added activities and focus on their high value added activities. It also helps organization
save their time and energy which leads to more efficient units. The idea of outsourcing is more
important for project based organizations where the nature of works is different from a
particular project to another one. This paper presents an integrated balanced score card system
with an adaptation of ELECTRE III method to select suitable resources for outsourcing. The
proposed model of the paper is implemented for a case study of subway system in Iran and the
results are discussed.