The most popular approach for solving fully fuzzy linear programming (FFLP) problems is to convert them into the corresponding deterministic linear programs. Khan et al. (2013) [Khan, I. U., Ahmad, T., & Maan, N. (2013). A simplified novel technique for solving fully fuzzy linear programming problems. Journal of Optimization Theory and Applications, 159(2), 536-546.] claimed that there had been no method in the literature to find the fuzzy optimal solution of a FFLP problem without converting it into crisp linear programming problem, and proposed a technique for the same. Others showed that the fuzzy arithmetic operation used by Khan et al. (2013) had some problems in subtraction and division operations, which could lead to misleading results. Recently, Ezzati et al. (2014) [Ezzati, R., Khorram, E., & Enayati, R. (2014). A particular simplex algorithm to solve fuzzy lexicographic multi-objective linear programming problems and their sensitivity analysis on the priority of the fuzzy objective functions. Journal of Intelligent and Fuzzy Systems, 26(5), 2333-2358.] defined a new operation on symmetric trapezoidal fuzzy numbers and proposed a new algorithm to find directly a lexicographic/preemptive fuzzy optimal solution of a fuzzy lexicographic multi-objective linear programming problem by using new fuzzy arithmetic operations, but their model was not fully fuzzy optimization. In this paper, a new method, by using Ezzati et al. (2014)’s fuzzy arithmetic operation and a fuzzy version of simplex algorithm, is proposed for solving FFLP problem whose parameters are represented by symmetric trapezoidal fuzzy number without converting the given problem into crisp equivalent problem. By using the proposed method, the fuzzy optimal solution of FFLP problem can be easily obtained. A numerical example is provided to illustrate the proposed method.

In this paper a hybrid algorithm for solving bound constrained optimization problems having continuously differentiable objective functions using Fletcher Reeves method and advanced Genetic Algorithm (GA) have been proposed. In this approach, GA with advanced operators has been applied for computing the step length in the feasible direction in each iteration of Fletcher Reeves method. Then this idea has been extended to a set of multi-point approximations instead of single point approximation to avoid the convergence of the existing method at local optimum and a new method, called population based Fletcher Reeves method, has been proposed to find the global or nearer to global optimum. Finally to study the performance of the proposed method, several multi-dimensional standard test functions having continuous partial derivatives have been solved. The results have been compared with the same of recently developed hybrid algorithm with respect to different comparative factors.

In the Information and Communications Technology era, eGovernment projects present a great opportunity for governments to offer better and quicker services to their users from the public. However, the success and the failure of these projects to achieve the expected goals depend heavily on some important aspects; mainly websites usability. This study intends to evaluate usability of current e-government websites in Taiwan. The results indicate that a number of usability problems have been found in the target e-government websites. These findings can help designers identify users’ usability requirements and draw their particular attention to further develop more usable e-government websites.

Risk management in construction industry in several cases is not only incomplete regarding the unification of Occupational Health and Safety (OHS) hazards, but it is also incomplete in not having a systematic and innovative method to assess the impacts of these risks on the objectives of a project. An integrated hybrid Fuzzy Inference System-Latin Hypercube Simulation for the evaluation of OHS risks in construction projects is presented in this paper. Prioritization of safety risks systematically without human interference with fuzzy inference system gives the appropriate response to the identified risks. An advanced Monte Carlo simulation is also used for the evaluation of quantitative objectives of a project. This approach allows us to get away from discrimination and simulate the risks with high impacts but with low probabilities. In order to measure the relationship between the occurrences of each of the risks impacts on project objectives, the sensitivity analysis based on Pearson correlation coefficient is used to determine the usefulness of the proposed integrated hybrid method.

Supply chain management is important for companies and organizations to improve their business and lead competitiveness in the global marketplace. But demand variations in the supply chain are significant problem for most practitioners, planners, demand managers, and operations managers. Demand variations make forecasting and inventory management more difficult and tend to increase inventory levels. The supply chain (SC) profitability can be affected by the cost associated with large inventories, transportation, and production due to the bullwhip effect. Only bullwhip effect can lead to reduce the supply chain profitability in great amount. This paper represents a computational intelligence approach, which addresses the bullwhip effect in multistage supply chain. As a computational intelligence approach, Genetic Algorithm (GA) is employed to reduce the bullwhip effect. Through this approach, optimal order quantity in each stage is to be calculated by considering cost associated with bullwhip effect. Distorted information from one end of a supply chain can lead to tremendous inefficiencies to other end. In this paper it is shown that if each player of the supply chain orders or transfers optimum quantities for the upcoming period then the bullwhip effect can be reduced significantly.

The main objective of this study is to identify the most important criteria and indicators in selection of business intelligence vendors, and ranking the vendors of such tools using Fuzzy Analytical hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), to compare results of these two methods and to provide appropriate solutions for the sample company, namely National Iranian Oil Company (NIOC).
Spearman & apos; s rank correlation test was used for comparing the methods and determining their correlation. A strong positive correlation was observed between the ranks of business intelligence tools at the significance level of 0.05 in both methods. The results of the ranking by means of FAHP method show that IBM Company was the best one, followed by Oracle, SAS, QlikTech, SAP and Microsoft. However, based on the FTOPSIS method, Oracle was the leading company, followed by IBM, SAS and SAP and finally Microsoft.

This study aims to investigate the impact of social networking sites advertisements on consumer purchase decisions. It also seeks to examine how brand awareness mediates this primary effect. The data for this study was collected based on 360 followers from student's perspectives towards major apparel brands across Girne American University in North Cyprus. Data analysis was performed using structural equation modeling (SEM) in order to analyze the data collected. The study found that SNS advertisement had a significant impact on brand awareness, alongside consumer purchase decisions. Similarly, it found support for the mediating role of brand awareness. This research extends prior research by investigating the mediating effect of brand awareness between the SNS advertisements and purchase decision path. Finally, this study enriches social media marketing literature by providing evidence from North Cyprus.

Due to the importance and complexity of the portfolio management issue, over 100 different techniques have already been presented. In general, the final result of these tools is to create a prioritized list of the projects that must be selected for allocating resources. The use of financial strategies may be misleading in some cases, and it is necessary to combine these methods with other methods such as strategic approaches in order to guarantee a balanced portfolio toward the organizational strategies. On the other, categorizing projects into different baskets allows the organizations to select, evaluate and prioritize the projects in a subset using a set of similar criteria and techniques. In this article, by choosing agriculture sector as a case study, an attempt has been made to study the evaluation, ranking and management of projects with investment classifying strategy of the projects using Delphi, TOPSIS and AHP methods. The results reveal that in similar cases we can use the presented model by determining the type of activity and investment and localization of the indexes.

Manufacturing industries are consistently working on improving their operational performance to remain competitive in the market. LM is a well-recognized approach for improving the overall performance. It contains several elements covered under a few lean attributes. This paper presents the application of Graph Theory and Matrix Approach (GTMA) for the identification of relative importance of different lean attributes in a lean environment using qualitative and quantitative factors. The Lean Manufacturing Attributes (LMA’s), affecting the overall LM environment, of a manufacturing industry were identified and analyzed for the implications on the managerial decisions. .In this proposed study, The GTMA approach is applied to prioritize the LMA’s based on their relative importance.