Abolfazl Kazemi; Vahid Hajipour
Abstract
In today's competitive markets quality as a competitive advantage is important, but quality always comes with price, so cost of quality recognition and proper division has always attracted attention of many researchers in the literature. The related literature show that from the time quality costing ...
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In today's competitive markets quality as a competitive advantage is important, but quality always comes with price, so cost of quality recognition and proper division has always attracted attention of many researchers in the literature. The related literature show that from the time quality costing is introduced, all attentions were to identify the different costs of quality and sometimes there were different views to these costs which have similarities in the principle of classifications. Despite to successful reports provided for implementing these methods in identifying costs of quality, it can be seen a gap in improvement processes. Although the identification of costs and improvement projects in this field, often improve the level of products and service quality and ultimately lead to increased customer satisfaction, But certainly there is a significant difference between non-optimum and optimum resource allocation in receiving results. The aim of this study is to design an approach that reach to a certain quality level in a consistent and cost less way. In this approach, after identifying the types of quality costs, difference in importance of costs is determined. The first weight comes from financial results obtained from costs identification, indeed it is the proportion of the financial load of each cost to total quality costs. Stakeholder opinion based on BSC in second weight calculating process comes into AHP as expert group.
Maryam Azizi; Abolfazl Kazemi; Alireza Alinezhad
Abstract
Reverse logistics as a new approach and attitude in the area of logistics is one of the new trends in logistics management, recycling, and or reuse of products. Logistics network design in the forward and reverse mode is one of the most important issues that forms the strategic dimension of supply chain ...
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Reverse logistics as a new approach and attitude in the area of logistics is one of the new trends in logistics management, recycling, and or reuse of products. Logistics network design in the forward and reverse mode is one of the most important issues that forms the strategic dimension of supply chain design. In this paper we propose a mixed integer linear programming (MILP) model for reverse logistics problem. In the proposed model costs of facilities construction, transportation and procurement from suppliers are minimized and importance of suppliers are maximized. Since the proposed model is NP-hard, we use NSGA-II and NRGA algorithms to solve the problem.
Hamed Rahmani; Morteza Moosakhani; Gholamreza Memarzade Tehran; Karamollah Daneshfard; Abolfazl Kazemi
Abstract
Referring to a variety of media and news headlines, we can figure out the increase in the phenomenon of corruption in the country. One of the applied mechanisms by international organizations like international transparency and global bank is applying Governance Model to combat against Corruption. There ...
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Referring to a variety of media and news headlines, we can figure out the increase in the phenomenon of corruption in the country. One of the applied mechanisms by international organizations like international transparency and global bank is applying Governance Model to combat against Corruption. There are different theories about good governance and the most controversial one is the mechanism of social control. In this theory, an appropriate model for governance in government systems is the combination of police power (force), exchange and persuasion in a variety of organizations. The aim of this study is to identify this combination in different organizations to combat against corruption. The present study is a developed research kind that has utilized Fuzzy Inference System for identification the mixture of three forces. For constructing fuzzy rules in the present study, we have applied mixed method of Shannon entropy and Delphi analysis. Shannon entropy has been used for analyzing the coefficients of the components of corruption in the organizations and as an "if" part of the rules, furthermore Delphi analysis has been applied for analysis of the combination of the social control or as a "then" part of the rules. The results of the study were applied as an " if and then" rules for analyzing six areas of a model. The three areas, related to Grand Corruption, included law enforcement agencies, financial and normative as well as three other areas related to Petty Corruption including law enforcement organizations, financial and normative. These procedures were applied in Fuzzy Inference System and the results have been analyzed
Mojgan Khorasani; Abolfazl Kazemi
Abstract
This paper investigates a supplier evaluation and selection model which considers features of leagile supply chain and allocates orders to the selected suppliers. In the proposed model, potential suppliers are evaluated by applying a multi-objective model with respect to the key features of leagile supply ...
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This paper investigates a supplier evaluation and selection model which considers features of leagile supply chain and allocates orders to the selected suppliers. In the proposed model, potential suppliers are evaluated by applying a multi-objective model with respect to the key features of leagile supply chain, including the ability to respond to demands, reducing delay time and costs (which are the winning factors for being the winner of market in this supply chain), as well as considering the capacities and limitations of organizations and suppliers. The proposed model allows buyer to select several suppliers. In addition, the model is multi-products and multi-periods. Due to long time and inefficiency of exact methods for large-sized problems, in addition to Lingo software, Genetic Algorithm is used to achieve the optimum solution
Abolfazl Kazemi; Javad Ghasemi; Vahid Zandieh
Volume 9, Issue 23 , December 2011, , Pages 131-161
Abstract
Previously, decision about granting facilities to clients of banks in Iran were made based on personal judgment about the risk of failure in reimbursement. But, increasing demand for bank facilities by economic firms and households in one hand, and increasing extensive commercial competition among banks ...
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Previously, decision about granting facilities to clients of banks in Iran were made based on personal judgment about the risk of failure in reimbursement. But, increasing demand for bank facilities by economic firms and households in one hand, and increasing extensive commercial competition among banks and economic- credit companies in the country and their efforts to alleviate the risk of failure in reimbursement of facilities on the other hand, have resulted in using modern methods such as statistical methods in this area. Today, to predict the possibility of failure in reimbursement of facilities and to classify their applicants, banks use the credit ranking of their clients. Savings in time and costs, removing personal judgments and increasing the accuracy of evaluating applicants of various facilities are some of the benefits gained in this method.
There are various statistical methods such as audit analysis, logistic regression, nonparametric smoothing and other methods including neural networks which have been used in ranking the credits. Among these methods, neural network method is of higher flexibility and has attracted more attention in recent years due to its ability to classify, generalize and learn the patterns.
In this paper, firstly we select some of the important criteria in granting various credit facilities such as financing loan, civil partnership, installment sale and unilateral contract to natural clients of a private bank in the country using questionnaire and the opinions of elite people in the field of banking. Then, we classify them by
presenting four models of neural networks namely MOE, MLP, LVQ and RBF and evaluate the accuracy of the ranking of these models. The obtained results indicate that MOE model is more accurate compared to MLP and RBF models and LVQ has not acceptable accuracy for ranking the credits of bank applicants.
