Clustering is a popular data mining technique for grouping a set of objects into clusters so that objects in one cluster are very similar and objects in different clusters are quite distinct. K-means (KM) algorithm is an efficient data clustering method as it is simple in nature and has linear time complexity. However, it has possibilities of convergence to local minima in addition to dependence on initial cluster centers. Artificial Bee Colony (ABC) algorithm is a stochastic optimization method inspired by intelligent foraging behavior of honey bees. In order to make use of merits of both algorithms, a hybrid algorithm (MABCKM) based on modified ABC and KM algorithm is proposed in this paper. The solutions produced by modified ABC are treated as initial solutions for the KM algorithm. The performance of the proposed algorithm is compared with the ABC and KM algorithms on various data sets from the UCI repository. The experimental results prove the superiority of the MABCKM algorithm for data clustering applications.

Medical tourism industry is an international phenomenon, which most of medical tourists for some reasons such as high costs of treatment, long waiting queues, lack of insurance and lack of access to health care in the origin country, travel long distances to benefit from health care services of destination country. Given the competitive nature of this industry, most countries are designing practical and legal services and planning for their development. For this purpose, this study has been conducted to develop a strategic planning framework for development of medical tourism industry in Yazd province of Iran; because in recent years Yazd has recognized as the health pole by patients in developing countries. In sum, emphasizing on servicing, enhancing and developing specialized treatment centers, has attracted patients from center, south and east of the country as well as Middle East and Central Asia countries. The dominant approach in this study is developmental – practical and also the research method is descriptive, analytical and survey. In order to analyzing the data, the SWOT model and best-worst techniques have been used. In the following, after identifying strategic position of Yazd province in terms of medical tourism industry, the related strategies were formulated and practical results were presented.

Tourism infrastructure development in different regions of the world does not follow a symmetrically equal pattern. Because of the importance of infrastructure in the tourism development, the present research is an attempt to examine the hard elements of tourism infrastructure in different provinces of Iran, using the indicators proposed by Pearce and Wu (2015) [Pearce, P. L. & Wu, M. Y. (2015). Soft infrastructure at tourism sites: identifying key issues for Asian tourism from case studies. Tourism Recreation Research, 40 (1), 120-132.]. To accomplish this, the data registered in the statistical yearbook of the Statistical Center of Iran were investigated. The method of research was analytical survey. To analyze and rank the data collected from the yearbook, VIKOR and TOPSIS methods were employed. The results of the analysis show that Tehran Province was under the best conditions of the Iranian tourism infrastructure, whereas Ilam Province was under the worst condition. The results about the condition of hard tourism infrastructure in the provinces of Iran, next to their tourism potentials, can provide necessary data for the future planning of the industry.

The separation at the source of Municipal Solid Waste (MSW) is an initiative that facilitates the subsequent recycling work and contributes to palliate the negative impacts of the traditional unsorted collection system. This paper presents a multi-objective integer linear programming model of the determination of the optimal location of assorted waste bins in an urban area. We consider, jointly, the objectives of minimizing the investment cost and the average distance from the dwellings to the bins. The model was applied in simulated instances of an Argentinian medium-size city, contributing to the transition from the current door-to-door based system to a community bins system. To solve this problem, we apply both the weighting method, which has been used to solve similar problems in the literature, and a novel version of the augmented ε-constraint method (AUGMECON2). The results over simulated scenarios show that, in general, AUGMECON2 has a better performance, yielding a larger number of efficient solutions at lower computation times.

This study deals with the performance modeling and reliability analysis of a redundant machining system composed of several functional machines. To analyze the more realistic scenarios, the concepts of switching failure and geometric reneging are included. The time-to-breakdown and repair time of operating and standby machines are assumed to follow the exponential distribution. For the quantitative assessment of the machine interference problem, various performance measures such as mean-time-to-failure, reliability, reneging rate, etc. have been formulated. To show the practicability of the developed model, a numerical illustration has been presented. For the practical justification and validity of the results established, the sensitivity analysis of reliability indices has been presented by varying different system descriptors.

The present paper emphasizes on the development of a hierarchical model using Fuzzy Multiple Attribute Decision Making (FMADM) method for the selection of E-learning websites. The working of the model developed in this research mainly consists of three steps: (i) Summarization and identification of selection indexes, (ii) Selection indexes weights calculations using Fuzzy Analytical Hierarchy Process (FAHP) and (iii) Ranking of alternatives by implementing three MADM analytical methods as Complex Proportional Assessment (COPRAS), Visekriterijumsko Kompromisno Rangiranje (VIKOR) and Weighted Distance Based Approximation (WDBA). In order to demonstrate the applicability and utility of the proposed methods, an empirical example related to the selection of E-learning websites that are widely used to learn the ‘C’ Programming Language for the software development is carried out. In addition, the results of these three methods are also compared to analyze the critical aspects of the selection indexes. It strongly shows that the developed FMADM model of this paper could be an efficient and effective assessment tool.

In this paper, we propose an exponential-related function (ER) and develop an intuitionistic fuzzy TOPSIS model based on the function (IF-TOPSISEF) to solve multi-attribute decision making (MADM) problems in which the performance ratings are expressed in intuitionistic fuzzy sets (IFSs). The main advantage of this new approach is that the exponential-related function is able to represent the aggregated effect of the positive and negative evaluations in the performance ratings of alternatives based on the intuitionistic fuzzy set (IFS) data. It also serves as a mean for the computations of the separation measures of each alternative from the intuitionistic fuzzy positive and negative ideal solutions to determine the relative closeness coefficients. To demonstrate the effectiveness of the proposed method, the proposed IF-TOPSISEF is applied for the evaluation of the concept designs of a part in an HDD machine (The drill pipe slider), and for some hypothetical examples.

Tower cranes, on today’s typical building construction sites, are the centerpiece of production, hoisting and transporting of a variety of loads. Due to a simple crane limited capacity; there is an urgent need to use high capacity cranes such as tower cranes. However, we have to select an appropriate type of cranes to be utilized to reduce the associated coste as much as possible. In this research, we propose a method to select the suitable type of crane and locate the best place for crane erection based on a minimum radius for requested crane and minimum cost. To fulfill the target, a computer program is designed to numerate these problems, demonstrating an example explaining how to apply the program and the results are discussed.

Powder mixed electro discharge machining (PMEDM) is a hybrid machining process where the electrically conductive powder is mixed into the dielectric fluid to enhance the machining efficiency. In this investigation, PMEDM is performed for the machining of AISI 304 stainless steel when silicon carbide powder is mixed into the kerosene dielectric. Peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameter while material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) are considered as response. A face centered central composite design (FCCCD) based response surface methodology (RSM) is applied to design the experiment. A hybrid optimization technique like desirability coupled with fuzzy-logic method is performed to get the optimum level of the multiple performance characteristics. Analysis of variance (ANOVA) is performed for the statistical analysis. The result shows that peak current is the most significant parameter for MRR, TWR and Ra. The optimal setting for maximum MRR, minimum TWR and Ra have been obtained by desirability coupled with fuzzy-logic method.

It is very important to manage and control projects with the consideration of the triple constraints; namely time, cost and scope. It is also extremely important to manage the scope and all the procurements needed to complete any project. During the project’s lifecycle many changes take place, either positively or negatively, which should be controlled. If the changes are not controlled we may have scope creep that has negative effect on the project. It is commonly considered a negative incident, and thus, should be kept away from the project. By considering this concept, in this paper, we discuss scope change and managing scope and fuzzy analytical hierarchy process is used in selecting the best strategy to manage scope change in projects.