فصلنامه مطالعات مدیریت صنعتی
پیاپی 37 (تابستان 1394)

In this paper, supply chain network design problem is modeled as a fuzzy multi objective mixed integer programming which seeks to locate the plants, DCs, and warehouses by considering disruption, supply and demand risk. Maximizing net present value of supply chain cash flow, minimizing delivery tardiness and maximizing reliability of suppliers are considered as objective functions in the proposed mathematic model. In order to have a more reliable model in case of disruption, the robustness measure is used in the model. Moreover, because of the lack of information, the economic factors such as tax rate, interest rate, and inflation are considered as uncertain factors in the model. An interactive possibilistic programming approach is applied for solving the multi-objective model. To solve larger size instances, genetic algorithm is proposed. Finally numerical examples are presented to show how the model works in practice.

Newcomer companies, creating dynamism in the economy, as through the provision of goods, services and new technologies, increasing competition in the market and expanding the industry, making it more dynamic. But the fact that what was going on after their entrance are also important. Because their growth and longevity in achieving long- term goals and policies in regarding employment and economic growth are of particular importance. This study was conducted to investigate the factors that influence the survival of newcomer companies. Company size and growth rate of the industry are features that are assumed to affect the survival of the company. So the effects of these variables on the survival of newcomer companies of Electronic and Electric Industries in Mazandaran province during1981-2011 were studied.
Semi-parametric Cox regression model was used to test the hypotheses. In order to further analyze the data, nonparametric model life table and product limit estimator was used. Data from the Mazandaran province database of Industry, Mine and Trade were collected and for data processing, winTDA software is used. As a result of this study, a positive relationship between firm size and survival rates were approved. But there was no significant relationship between industry growth rates and survival.

Many of the companies in using the instruments and techniques of attaining lean production objectives have faced numerous problems due to the lack of a unified approach toward its implementation and evaluation means. Therefore, different researchers with regard to their own viewpoints have suggested different methods to establish and evaluate lean production in industries. In this regard, the purpose of the present research is to present a model for evaluating lean production in SMEs through the use of a combination of confirmatory factor analysis, cluster analysis, and PROMOTEE technique. The statistical population of the study consists of all the SMEs manufacturing primary and fabric metals in East Azarbaijan Province. For data collection, a researcher – devised questionnaire was used after its validity and reliability had been confirmed, The findings of confirmatory factor analysis indicate eight main constructs as the principal methods and instruments of lean production. Cluster analysis conducted by K-mean method also grouped the manufacturers in to three clusters. Finally, the performed ranking showed that the second, third, and first clusters are ranked first through third, respectively, from the viewpoint of their performance in lean production. The results of the research indicate that the industries that pay more attention to timely production, to suppliers, and to customers have better performance in lean production, too.

Performance of supply chain usually is measured through multiple-criteria. In this paper, an integrated model is proposed to plan a supply chain with three-echelons of supply, production, and distribution considering both logistic costs and service level, concurrently. A mixed-integer linear mathematical programming model with two objective functions, including minimizing logistic costs, and maximizing service level is developed. Goal programming method is used to solve the proposed multi-objective mathematical programming. Finally a real case study is analyzed in order to check the applicability of proposed model and the solution approach.

This paper presents a mathematical model for solving dynamic cell formation problem, operator assignment and the inter-cellular and intra-cellular layouts simultaneously. The proposed model includes three objectives, the first objective seeks to minimize inter and intra-cell part movement, machine relocation, second objective minimize operator related cost, third objective maximize ratio of consecutive forward flows. The model is Multi-objective; therefore, the LP-metric approach is used to solve it. In order to validate the model, the proposed model has been solved by using Lingo software. Then, due to NP-hardness of the cell formation problem, for solving large scale problems, a multi-objective simulated annealing algorithm proposed. Several numerical examples solved by Lingo software and multi-objective simulated annealing algorithm. Results show that the proposed multi-objective simulated annealing algorithm solved considerably time less than the software Lingo and also none of the answers obtained by the two methods are not dominated.

Risk is inherent and inseparable part of life and business. Always uncertainty condition arising from incomplete information and data or ungovernable variables, associated with opportunities and threats.Nowadays many organizations and companies have relied heavily on information systems and information security management has transformed to an important organizational topics. And due to the fact that the use of information systems security may be created some risks, an effective risk management process, will result in a successful security program. Risk management includes risk identification process, risk assessment and risk-reduction efforts to acceptable levels. The objective of this research is to prioritize information security risks, in order to provide a mechanism to enhance the security of enterprise information. To this end, a model has been presented for organizational information security risk assessment using the fuzzy AHP and Bayesian networks. In the assessment process, risks impact by fuzzy AHP and risks probability by Bayesian networks have calculated and finally The risks Prioritized. The findings suggest In the case study, the risk of lack of knowledge and lack of proper training in the field of information security, have the highest priority and attention is needed most.

The branches are more efficient to develop. This paper presents a model for evaluating the performance of the software companies that provide similar services to customers in various profound. Various parameters of the model to cover the interests of stakeholders, customers and ... To provide performance measurement systems in the Charter of the method used. Performance evaluation and assessment of various aspects such as the interests of employees, customers, shareholders and ... Is to be calculated. The performance of these branches according to the criteria developed by inconclusive data model of fuzzy data envelopment analysis to measure.