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.

Selection of material for a specific engineering component, which plays a significant role in its design and proper functioning, is often treated as a multi-criteria decision-making (MCDM) problem where the most suitable material is to be chosen based on a given set of conflicting criteria. For solving these MCDM problems, the designers do not generally know what should be the optimal number of criteria required for arriving at the best decisive action. Those criteria should be independent to each other and their number should usually limit to seven plus or minus two. In this paper, five material selection problems are solved using three common MCDM techniques to demonstrate the effect of number of criteria on the final rankings of the material alternatives. It is interesting to observe that the choices of the best suited materials solely depend on the criterion having the maximum priority value. It is also found that among the three MCDM methods, the ranking performance of VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) method is the best.

Ranking fuzzy numbers is one of the most important phases in any decision making process in fuzzy environments. In most cases, we deal with fuzzy numbers in the field of evaluating alternatives with fuzzy information or linguistic variables. This paper investigates ranking fuzzy numbers using the concept of preference ratio, introduces the weakness of this method, and proposes a new approach that overcomes the shortcoming of existing method. The proposed approach which is based on the concept of utility function takes the opinion of DM for ranking fuzzy numbers into account.

During the past few years, despite tremendous contribution on deterministic flow shop problem, there are only limited number of works dedicated on stochastic cases. This paper examines stochastic scheduling problems in two-machine flow shop environment for expected makespan minimization where processing times of jobs are normally distributed. Since jobs have stochastic processing times, to minimize the expected makespan, the expected sum of the second machine’s free times is minimized. In other words, by minimization waiting times for the second machine, it is possible to reach the minimum of the objective function. A mathematical method is proposed which utilizes the properties of the normal distributions. Furthermore, this method can be used as a heuristic method for other distributions, as long as the means and variances are available. The performance of the proposed method is explored using some numerical examples.

Portfolio optimization problem follows the calculation of investment income per share, based on return and risk criteria. Since stock risk is achieved by calculating its return, which is itself computed based on stock price, it is essential to forecast the stock price, efficiently. In this paper, in order to predict the stock price, grey fuzzy technique with high efficiency is employed. The proposed study of this paper calculates the return and risk of each asset and portfolio optimization model is developed based on cardinality constraint and investment income per share. To solve the resulted model, Invasive Weed Optimization (IWO) algorithm is applied. In an example this algorithm is compared with other metaheuristic algorithms such as Imperialist Competitive Algorithm (ICA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The results show that the applied algorithm performs significantly better than other algorithms.

Selection of an appropriate supplier along with planning a good inventory system has become an area of open research for the past few years. In this paper, we present a multi objective decision making supplier and inventory management model where two objectives including the quality and offering price of supplier are minimized, simultaneously. The proposed model is formulated as mixed integer programming and it is converted into an ordinary single objective function using Lp-Norm. In order to find efficient solution, we use NSGA-II as meta-heuristic technique and the performance of the proposed model is examined using some instances. The preliminary results indicate that both Lp-Norm and NSGA-II methods can be used to handle problems in various sizes.

This paper empirically investigates the impact of exchange rate volatility on the real exports in India using the ARDL bounds testing procedure proposed by Pesaran et al. (2001). Using annual time series data, the empirical analyses has been carried out for the period 1970 to 2011. The study results confirm that real exports are cointegrated with exchange rate volatility, real exchange rate, gross domestic product and foreign economic activity. Our findings indicate that the exchange rate volatility has significant negative impact on real exports both in the short-run and long-run, implying that higher exchange rate fluctuation tends to reduce real exports in India. Besides, the real exchange rate has negative short-run and positive long-run effects on real exports. The empirical results reveal that GDP has a positive and significant impact on India’s real exports in the long-run, but the impact turns out to be insignificant in the short-run. In addition, the foreign economic activity exerts significant negative and positive impact on real exports in the short-run and long-run, respectively.

An important problem in control chart implementation is the availability of resources to collect and analyze data for control charts implementation. This paper proposes a method to prioritize and select final product parameters to control. The prioritization is based on cost of quality and technical criticality of those parameters. The prioritization method is demonstrated by a case study of flexible printed circuit manufacturing.

Leagile supply chain management has emerged as a proactive approach for improving business value of companies. The companies that face volatile and unpredictable market demand of their products must pioneer in leagile supply chain strategy for competition and various demands of customers. There are literally many approaches for performance metrics of supply chain in general, yet little investigation has identified the reliability and validity of such approaches particularly in leagile supply chains. This study examines the consistency approaches by confirmatory factor analysis that determines the adoption of performance dimensions. The prioritization of performance enablers under these dimensions of leagile supply chain in small and medium enterprises are determined through fuzzy logarithmic least square method (LLSM). The study developed a generic hierarchy model for decision-makers who can prioritize the supply chain metrics under performance dimensions of leagile supply chain.