Decision making problem is the process of finding the best option out of all feasible alternatives. There are some methods for solving Multiple Criteria Decision-Making problems and Simple Additive Weighting (SAW) is one of the most popular ones. In this paper, among multi-criteria models in making complex decisions and multiple attribute models for the most preferable choice, SAW technique is extended using interval numbers. For this purpose, we first propose a method for extending Entropy method for dealing with interval data, and then the extended SAW method with interval data is proposed by using the interval weights derived by the proposed interval Entropy method. The extended SAW method is an algorithm to determine the most preferable choice out of all possible choices, when the input data are stated in interval.

In this paper, a new multi-item inventory system is considered with random demand and random lead time including working capital and space constraints with three decision variables: order quantity, safety factor and backorder rate. The demand rate during lead time is stochastic with unknown distribution function and known mean and variance. Random constraints are transformed to crisp constraints with using the chance-constrained method. The Minimax distribution free procedure has been used to lead proposed model to the optimal solution. The shortage is allowed and the backlogging rate is dependent on the expected shortage quantity at the end of cycle. Two numerical examples are presented to illustrate the proposed solution method.

It is necessary for companies and industries to select the most appropriate maintenance strategy to increase the reliability and safety level with reasonable cost. The primary objective of this paper is to assess different maintenance strategies and to select the best and the most appropriate alternatives for Saipa vehicle industry in Tehran, Iran. For this purpose, we simultaneously consider numerous conflicting objectives and constraints. In this study to counter with this conflicting and to consider the dependency among the qualitative and quantitative criteria and sub-criteria, an integration of Analytic Network Process (ANP) and fuzzy set theory are considered. Therefore, factors playing important role in selecting the best maintenance strategy are determined by reviewing the research literature and interviewing with the experts by Delphi technique. Considering the relations among different factors, a network with 4 criteria and 28 sub-criteria are proposed. In the next step, ANP technique is applied for ranking effective factors in evolution of appropriate maintenance strategy. Results reveal that the best maintenance strategy for fixture body of pride (setter) is corrective maintenance.

In this paper, we study a supply chain problem where a whole seller/producer distributes goods among different retailers. The proposed model of this paper is formulated as a more general and realistic form of traditional vehicle routing problem (VRP). The main advantages of the new proposed model are twofold. First, the time window does not consider any lower bound and second, it treats setup time as separate cost components. The resulted problem is solved using a hybrid of particle swarm optimization and simulated annealing (PSO-SA). The results are compared with other hybrid method, which is a combination of Ant colony and Tabu search. We use some well-known benchmark problems to compare the results of our proposed model with other method. The preliminary results indicate that the proposed model of this paper performs reasonably well.

In the contexture of a customer-driven goods or service design process, a well-timed update of customer’s requirements may not only serve as a necessity indicator to observe how things change over time, but also it incorporates the firms a better ground to interoperate different strategies to meet the future needs of its customer. This paper proposes a systematic methodology to deal with the customer needs’ dynamics, in terms of their relative weights, in the QFD. Compared with previous research, the contribution of this paper is fourfold. First, it applies some linguistic variables to get preferences of customers and experts to determine the relative importance of customer requirements (CRs) and the relationships between customer requirements and engineering characteristics (ECs). Second, it proposes the implementation of a forecasting technique. Third, it describes more comprehensively on how future uncertainty in the weights of customer’s needs could be estimated and transmitted into the design attributes. Fourth, it proposes the implementation of a quantitative approach, which takes into account the decision maker’s attitude towards risk to optimize the QFD decision making analysis. Finally, a real-world application of QFD is provided to demonstrate the practical applicability of the proposed methodology.

This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model.

Cultural intelligence (CQ) is a new area of research, which is considered in different areas including banking industry. In this paper, we design a questionnaire in Likert scale and measure CQ in banking industry. The proposed study of this paper distributes 53 questionnaires among 60 employees of bank Sarmyeh, which is one of the private banks in Iran. The study also distributes a standard questionnaire among them to measure the performance of the same employees. Cronbach alpha are calculated for both questionnaires as 0.8155 and 0.9421, respectively. The study calculates Pearson correlation ratio between these two items and the result indicates that there is a positive (0.41) and meaningful relationship between CQ and performance measurement. In addition, there is a positive and meaningful relationship between motivational CQ and performance measurement (0.378). However, the survey does not find any meaningful relationship between cognitive CQ, metacognitive CQ and behavioral CQ on one side and performance measurement.

Women play important role on building a sustainable family oriented society; they could also contribute to society by contributing to labor market. However, women’s personal characteristics such as educational background, years of experience, etc. could impact their future occupations. In this paper, we study the impact of various factors on women’s job status. The measurement tools for social factors of employment in this research is a questionnaire consists of 32 questions. The study measures the reflection of repliers to different social factors including social position, popularity, socialize, social manners, self-reliance, speech abilities, responsibility, etc. Data were gathered from a sample of 300 people using random sampling and analyzed using descriptive mono factor statistics, Spearman correlation, Kramer correlation coefficient, Chi-square, regression and path analysis. The validity of questionnaire is tested by using Cronbach alpha (%75). The results indicate that there are some meaningful relationships between woman’s educational level, age, residency status, socialization capability, urbanity, skill & ability and their employment. The study, however, does not find any relationship between marital status and number of children and outcome of woman’s employment.

Customer satisfaction plays an important role on the success of banking industry. A customer may switch his/her primary banking from one to another as soon as he/she is unsatisfied from the quality of services. In this paper, we study the impact of six factors on electronic banking including easy access, design, transaction speed, security, information content and customer support on customer satisfaction. The proposed study was performed in different branches located in north east of city of Tehran, Iran named Tejarat. The study selected a sample of 200 customers, designed, and distributed a questionnaire among them. The results of our survey have indicated that all six components significantly influenced on customer satisfaction. We have also investigated a linear regression between the six independent variables and customer satisfaction and using stepwise linear regression technique the most suitable regression model. The results of regression analysis have also indicated that an increase of one unit in easy access, information content and customer support will increase customer satisfaction by 0.201, 0.368 and 0.356, respectively.

In this study, we investigate whether transactional analysis (TA) training could improve social adjustment in a case study of women with spouses with drug addiction. This experimental study was performed on 40 people who were addicted to drugs and were under medication in some clinical centers in city of Esfahan, Iran. The patients were randomly divided into two groups (control and an experimental group). The experimental group was trained under transactional training for 8 one-hour sessions. Cronbach alpha was calculated as 0.89, which is well above the minimum acceptable. The results of the survey show that the means of two groups before test are close to each other. However, after TA has been accomplished, there is meaningful difference between these two groups. The result of F-value statistical test is also meaningful when the level of significance is five percent. In other word, there are some evidences to believe that transactional analysis training impacts on our surveyed people, positively.