Fatemeh haghighat; Fariborz Golai
Abstract
In order to predict the values of passengers movement indexes which enjoy seasonal changes, this research uses Holt Winters Markov chain model, which is a combination of Markov chain and Holt Winters models. In this regard, Data on the number of moved passengers and the number of made trips indexes are ...
Read More
In order to predict the values of passengers movement indexes which enjoy seasonal changes, this research uses Holt Winters Markov chain model, which is a combination of Markov chain and Holt Winters models. In this regard, Data on the number of moved passengers and the number of made trips indexes are analyzed in Bushehr Province during the seasons of 1387 to 1391. First, Data on the each indexes of the studied intervals divided into two parts, then the second part data were predicted using Holt Winters model. In the next step, by calculating and classifying the errors of the actual and predicted values, Holt Winters Markov chain model is used in order to predict the Index values based on probabilities of errors mode and also improve the performance of Holt Winters model in prediction. The results obtained from the Comparison of two models of Holt Winters and Markov chain Holt Winters shows that Holt Winters Markov chain model is more accurate at predicting
Yalda Yahyazade; Laya Olfat; Maghsod Amiri
Abstract
Appropriate management of supply chain is one of the issues facing economic firms that affect all the organizational activities in order to produce the goods and provide the services. Consequently Supplier selection due to involvement of various qualitative and quantitative criteria such as quality, ...
Read More
Appropriate management of supply chain is one of the issues facing economic firms that affect all the organizational activities in order to produce the goods and provide the services. Consequently Supplier selection due to involvement of various qualitative and quantitative criteria such as quality, price, flexibility and delivery times is very difficult and complex and requires accurate and appropriate tools. On the other hand today's competitive environment due to its variable nature, has added the uncertainty and ambiguity in decision-making. The problem of supplier selection is not an exception as well and it seems suitable to use the robust optimization methods in such circumstances. The mentioned method is used in this research with the goal of supplier selecting and determining the amount order of products considering all restrictions in order to minimize the costs and maximize the utility of purchase in the condition of uncertainty. In this paper, a multi-objective deterministic model is presented to solve the problem, and then the deterministic model is converted to the robust model using the scenario-based robust method and then is solved using the LP metric method so optimal amount of order is obtained from each of suppliers at any period. To determine the weight of each of suppliers, Analytical Hierarchy Process (AHP) is used as well.
Abas Fadaei; Masood Rabieh; Mostafa Zandieh
Abstract
Considering that the active companies in the field of oil, gas,petrochemical and other energies are project-based and also theincrease of gas applicants who have taken policy of replacing the gasinstead of other fossil fuels, have imposed certain condition onorganizations and project managers in the ...
Read More
Considering that the active companies in the field of oil, gas,petrochemical and other energies are project-based and also theincrease of gas applicants who have taken policy of replacing the gasinstead of other fossil fuels, have imposed certain condition onorganizations and project managers in the Gas Company.One of themost important problem in the issue of project management is projectportfolio selection which is defined one of the most importantactivities in many organization such as gas organization. In this studyat first the effective indicators on projects are extracted by using theliterature and interviews with the experts of gas industry then themathematical robust multi objective model is provided by consideringthe uncertainty and unreliability in some parameters of model. Thismodel is solved by using Non-dominate Sorting Genetic Algorithmfor 20 degree of risk-taking decision Gama ( , Ct Bt ).At the end forhelping in decision making the TOPSIS technique is used forproviding a specific answer in Pareto Front .
Kaveh Khalili Damghani; Mohammad TaghaviFard; Kiaras Karbaschi
Abstract
The main goal of this paper is to evaluate the relative efficiency of each level of customer services in MELLI bank branches. A three stage process is defined as consecutive results of service provision to the customers. This process consists of sub-process such as customer expectations, customer satisfaction, ...
Read More
The main goal of this paper is to evaluate the relative efficiency of each level of customer services in MELLI bank branches. A three stage process is defined as consecutive results of service provision to the customers. This process consists of sub-process such as customer expectations, customer satisfaction, and customer loyalty. A hybrid method based on Multi-criteria Satisfaction Analysis (MUSA) and network Data Envelopment Analysis (DEA) is proposed to evaluate the relative efficiency of 30 branches. In this way, first the customer satisfaction was measured through a direct questionnaire based on customers perceptions analysis and quantified using MUSA method. Then, the customer satisfaction scores and the other important evaluating criteria such as number of employees, average evaluation scores of staff, operating costs, the amount of deposits, total credit facilities, the number of new checking accounts, expectations and customer loyalty were considered in DEA model as inputs and outputs. A three-stage DEA model was used to evaluate the efficiency of bank branches. The proposed DEA model was based on multipliers perspective, output-oriented with constant return to scale. The proposed three-stage DEA model quantified and assessed the efficiency of customer expectations, customer satisfactions, and customer loyalties in branches. The results showed that the mean relative efficiency of selected branches in three sub-processes namely customer satisfaction, operational results and customer loyalty were 83%, 94%, and 90%, respectively. The mean efficiency of the overall process is 89%.And four branches (about 13% of sample) were placed on efficient frontier for all sub-processes. Based on research findings, the branches which have been efficient in customer expectations were also efficient in other sub-processes and the main process.
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 ...
Read More
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
Mehran Khalaj; Amir Hossine Khalaj; Jalal Talebi
Abstract
Manufacturing systems are always facing different kinds of risk such as failure and interruption risk. Performance risk analysis of manufacturing systems cause errors happening in the prediction of parameters and will also result in wrong decisions where the real and appropriate data is not available. ...
Read More
Manufacturing systems are always facing different kinds of risk such as failure and interruption risk. Performance risk analysis of manufacturing systems cause errors happening in the prediction of parameters and will also result in wrong decisions where the real and appropriate data is not available. In uncertainty condition there is no appropriate data for decision making and in the specific mode of uncertainty the decision maker faces with a lack of information. Risk is a state of uncertainty that the available information from background of system is incomplete. Risks in manufacturing systems are directly related with failure to achieve the reliability of machines. So in this paper the records and the relationship between risk and reliability have been studied, then a model is proposed using Dumpster-Shafer theory to maximize the reliability according to the existing risk. Since the exact calculation of reliability for complex systems and processes is extremely difficult and complicated when the correct data of failure is not available, newly proposed model uses Dumpster-Shafer theory that enjoys all the available data for decision making instead of using the purely qualitative methods. Using this method results in obtain the risk ranges for equipment and machinery. These ranges are drawn in a risk analysis matrix according to the relationship between risk and reliability of machinery and the changes have been determined in order to meet the lower risk. All the proposed methods are examined using the data of a manufacturing company, the concentration of evaluating the reliability is on using the Probability theory in which the failure time is predicted by determining type of component failure distribution while the research provides change in attitude for applying the simultaneous use of possibility and probability theory
Ali Bonyadi Naeini; Saeed Yousef; Mohammad Ali Faezirad
Abstract
Today evaluation of customers to classify the quality of providing services is one of the main challenges of decision-makers in different organizations. It is difficult to respond to all customers’ demands because of increasing volume of them. On the other hand, in current competitive markets, ...
Read More
Today evaluation of customers to classify the quality of providing services is one of the main challenges of decision-makers in different organizations. It is difficult to respond to all customers’ demands because of increasing volume of them. On the other hand, in current competitive markets, customers are considered as capital of organizations. This issue results in purposefully study on different groups of customers in competitive markets. One of the effective ways to study the customers and provide the optimism service to them is grouping the market and clustering the customers. In this research first customers classified in appropriate clusters using neural network techniques SOM in order to provide purposefully service , so each customer can deliver proper service according to its cluster. Then by the proposed model in the paper the membership of each client in the appropriate cluster can be predicted by using DEA-DA technique. This model has provided dynamic clustering process for organizations so that by which new customers will be assessed at any moment and their proper cluster is determined with reasonable accuracy.
