Quality of services in banking industry plays essential role in measuring the performance of banks. As customer awareness increases on the services offered by banks, expectations from service quality increases too. Presently, managers of banks use different financial factors such as deposits, credits, etc. to rank their banks. This paper uses SERVQUAL technique to measure customer satisfaction for 14 branches of a bank in city of Kermanshah, Iran. The study first statistically shows that customer satisfaction was not the same for all these banks and then using analytical hierarchy process and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) ranks these branches using five components of SERVQUAL method; namely tangibles, reliability, assurance, responsiveness and empathy.

Selection of industrial robots for the present day’s manufacturing organizations is one of the most difficult assignments due to the presence of a wide range of feasible alternatives. Robot manufacturers are providing advanced features in their products to sustain in the globally competitive environment. For this reason, selection the most suitable robot for a given industrial application now becomes a more complicated task. In this paper, four models of data envelopment analysis (DEA), i.e. Charnes, Cooper and Rhodes (CCR), Banker, Charnes and Cooper (BCC), additive, and cone-ratio models are applied to identify the feasible robots having the optimal performance measures, simultaneously satisfying the organizational objectives with respect to cost and process optimization. Furthermore, the weighted overall efficiency ranking method of multi-attribute decision-making theory is also employed for arriving at the best robot selection decision from the short-listed competent alternatives. In order to demonstrate the relevancy and distinctiveness of the adopted DEA-based approach, two real time industrial robot selection problems are solved.

Flexible manufacturing system (FMS) is an important component of competitive strategy, which could be used for improving organizational performance, productivity, and profitability. The goal of this research is to use DEMATEL approach for finding the intensity of influence of selected criteria. Then, in order to evaluate flexible manufacturing systems, the results of DEMATEL are used in SAW method. A questionnaire was developed and ten professional experts working in various departments of Aluminum Composite Panel Industry are asked to answer its questions. The obtained results reveal that in this case, it is a better choice not to implement and develop FMS.

Weather forecast has been a major concern in various industries such as agriculture, aviation, maritime, tourism, transportation, etc. A good weather prediction may reduce natural disasters and unexpected events. This paper presents an empirical investigation to predict weather temperature using minimization of continuous ranked probability score (CRPS). The mean and standard deviation of normal density function are linear combination of the components of ensemble system. The resulted optimization model has been solved using particle swarm optimization (PSO) and the results are compared with Broyden–Fletcher–Goldfarb–Shanno (BFGS) method. The preliminary results indicate that the proposed PSO provides better results in terms of CRPS deviation criteria than the alternative BFGS method.

Selecting from a pool of interdependent projects under certainty, when faced with resource constraints, has been studied well in the literature of project selection problem. After briefly reviewing and discussing popular modeling approaches for dealing with uncertainty, this paper proposes an approach based on chance constrained programming and utility theory for a certain range of problems and under some practical assumptions. Expected Utility Programming, as the proposed modeling approach, will be compared with other well-known methods and its meaningfulness and usefulness will be illustrated via two numerical examples and one real case.

There is a high risk of R & D based innovation being commercialized, especially in the innovation transfer process which is a concern to many entrepreneurs and researchers. The purpose of this research is to develop the criteria of R & D commercialization capability and to propose a combined technique of Structural Equation Modelling (SEM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for R & D project evaluation. The research utilized a mixed-method approach. The first phase comprised a qualitative study on commercialization criteria development though the survey research of 272 successful entrepreneurs and researchers in all industrial sectors in Thailand. The data was collected with a structured questionnaire and analyzed by SEM. The second phase was involved with SEM-TOPSIS technique development and a case study of 45 R & D projects in research institutes and incubators for technique validation. The research results reveal that there were six criteria for R & D project commercialization capability, these are arranged according to the significance; marketing, technology, finance, non-financial impact, intellectual property, and human resource. The holistic criteria is presented in decreasing order on the ambiguous subjectivity of the fuzzy-expert system, to help with effectively funding R & D and to prevent a resource meltdown. This study applies SEM to the relative weighting of hierarchical criteria. The TOPSIS approach is employed to rank the alternative performance. An integrated SEM-TOPSIS is proposed for the first time and applied to present R & D projects shown to be effective and feasible in evaluating R & D commercialization capacity.

Clustering cellular manufacturing plays an important role in many industrial engineering problems. This paper investigates the performance of two methods of heuristic and metaheuristics fuzzy clustering. The proposed method investigates heuristic well-known FCM and particle swarm optimization (PSO) on some well-known benchmarks. We use two criteria of J(P) as well as Xie-Beni to compare the results. Three parameters of PSO method is tuned using design of experiment and then the results of PSO are compared versus FCM method in terms of two mentioned criteria. The proposed models are run for each instance 10 different times and, using ANOVA test, the means of two methods are compared. While the results of ANOVA do not indicate any meaningful difference between PSO and FCM in terms of J(P), we have found some meaningful differences between PSO and FCM in terms of Xie-Beni criterion. In other words, PSO performs better than FCM in terms of Xie-Beni.

This paper presents a two-stage hybrid flow shop scheduling problem with setup and assembly operations. The proposed study of this paper considers one kind of product with a quantity of demand where each product is made by assembling a set of different parts. At first, the parts are manufactured in a two-stage hybrid flow-shop and then the parts are assembled into products on assembly stage. Setup operations are needed when a machine starts processing the parts or it changes items. The considered objective is minimizing the completion time of all products. Since the problem is classified as NP-hard class, a combinatorial algorithm is proposed. The proposed algorithm is a three-step procedure where we use heuristic, genetic algorithm (GA), simulated annealing (SA), NEH and Johnson’s algorithm. Three lower bounds are presented and improved to evaluate the proposed algorithms. An extensive computational experiment is conducted to compare the performances of the proposed algorithms.

The Purchasing Power Parity (PPP) theory, which serves as a key to the determination of several models of exchange rates, suggests a long-term relationship between exchange rates and relative prices. It states that the price levels in all the countries are the same when measured in terms of a single currency. The purpose of this study is to model the behavior of the exchange rates of five partner countries of Tunisia, namely, (Germany, the United States, France, Italy, the UK, Morocco and Libya) relative to its fundamentals over the period 1990-1999. Beyond the traditional linear cointegration, we use the approaches based on fractional cointegration. We are trying to discriminate between the adjustment dynamics with long memory (but linear) and a dynamics of a short memory (nonlinear). Given the important role of the exchange rates in the successful experience of open economies, we are interested, in this work, in analyzing the dynamics of the exchange rates in the long run. The econometric results obtained through the GPH tests, make us consider the PPP as an event in the long run if significant short-term deviations from the PPP cannot exist. Therefore, the analysis of the fractional cointegration makes the deviations, regarding equilibrium, follow a slightly integrated process and therefore capture a much wider group of research parity or mean-reverting behavior.

The article presents solution procedure of geometric programming to solve the structural model with imprecise coefficients. We have considered a single objective structural optimization model with weight as an objective function. Geometric programming provides a powerful tool for solving a variety of imprecise optimization problems. Here we use nearest interval approximation method to convert a triangular fuzzy number to an interval number. In this paper, we transform this interval number to a parametric interval-valued functional form and then solve the parametric problem by geometric programming technique. The advantage of this technique is that we can find directly optimal solution of the objective function without solving two-level mathematical programs. Numerical example is given to illustrate the model through this approximation method.