MODERN RESEARCHES IN DECISION MAKING
Year:2016 | Volume:1 | Issue:2|Papers Count:8

In this paper, the set covering issue is used for location of emergency centers. In order to locate these centers in an optimum manner, a developed multi-objective model was used while considering objectives such as minimizing of the establishment cost of relief stations, maximizing the total covered population and minimizing the total distances between demand locations and allocated service providers. Since each of the centers has only an ambulance and these ambulances are out of reach during providing services, possible limitations have been used in this model. So, in this research, a combination of multi-objective decision making (MODM) methods and a set covering problem (SCP) is used for the location of relief centers in 18 districts of region 6 in Tehran. The selected solution is the simulated annealing method that is performed by using MATLAB software. At the end, the model related with the Ultra Innovative optimization algorithm of particle mass is used in order to compare with the answers of the Simulated Annealing Algorithm. Results show that both algorithms give the same answers for intended locations.

Determining the optimal and sustainable strategies to protect critical and sensitive systems is one of the main objectives of the organizations. To achieve this goal, efficient and stable strategies have to be determined. In this paper, with the aim of improving reliability, a pattern for modeling optimal strategies to defend and attack in the stable state is first presented, in which the defender to deceive the attacker provides a number of false targets. In the static model, a nonlinear programming model is proposed to determine the amount of investment in defend and attack of all sub-systems with respect to the probability of a successful attack, attacker capability in identifying false targets and game theory approach to find the balance point. Then, according to the results of the suggested static model, system dynamics and implications of evolutionary game theory, a new and dynamic approach to determine stable strategies of defense and attack is introduced. With respect to the proposed model, evolutionary stable strategy over time is examined for the defender based on the use or nonuse of false targets in view of attacker (including attacking or not attacking) and system. Finally, presented model is used for a numerical case and its final findings are analyzed.

Bank facilities, as one of the most important functions of banks, are of high significance to the survival of banks. The importance of identifying facility consumers is as much as, if not less in any way as, identifying deposit customers. In previous studies, the importance of such customers has not been well considered. This study mainly aims at reducing the problems related to providing suitable facilities to the customers and designing a recommender system for bank facilities by using previous data related to the facilities registered in a selected and large bank of the country. The presented system considers groups of customers during a training and validation programme by using facilities data and the information of customers’ accounts and provides the possibility of predicting customer’s condition for receiving future facilities. In order to design a recommender system, suitable data mining methods along with relevant validation procedure by each method have been selected and the final system has determined an appropriate direction for bank towards clients demanding facilities, with low error. The designed system helps bank managers in decision-making for granting more precise facilities. This system also helps banks to make maximum profits and reduce the costs related to claims collection and adopt a suitable procedure for each customer.Finally, the recommender system was presented to the supervisors of bank. Supervisors have provided some feedbacks for improving the final solution.

Pallets Management in industries whose supply chain is largely dependent on pallet is introduced as one of logistic parts. Pallet Management System is the system which is designed to deliver required pallets of suppliers at the right time and place in pallet industries. Pallet Management System fleet size, system responsiveness and cycle time are important indexes in assessing system performance. The objective of this study is to develop a model for pallet management system with risk pooling approach in SAIPA Automotive Group In this paper, after specifying the components of pallet management system and the relationship among the components through reviewing the research literature, the strategic impacts of risk pooling on the components have been studied and a model has been introduced to explain the state of the system after implementing the strategy in SAIPA corporation supply chain with simulation technique through employing MATLAB software. Results obtained from the simulation show that for implementation of the risk pooling approach in the system under study, a warehouse with the capacity of 1038 pallets is needed. The method of data collection is to review documents and literature as well as interviews with well-formed people. For data analysis, the discrete-event simulation method is used

Organizations, like living organisms, have life cycles. One day, they are born, grow and die another day. This article which is the output of a research, seeks to examine the situation of life cycle of academic staff in Humanities Faculty of Khalij Fars University. The main purpose of this research is to understand how the life cycle of the academic staff is, then based on the results, it can be predicted that what path it should pass in future. In this line, by reviewing the literature, 23 organizational growth models were identified. By studying these models, it was tried to develop a model relevant to an educational and research center (university). After developing the model, the next step was to develop a four-stage algorithm for gathering and analyzing the data. At the end, the algorithm introduced two indicators including mathematics index and fuzzy index. Based on these two indicators, it has been known that the life cycle of academic staff in the Faculty of Humanities of Khalij Fars University is at the end of the first stage, i.e. childhood during the period 2003 to 2014.

Supplier selection plays a key role in the organizations because the costs of the raw materials constitute the main part of the final product cost. Today, selecting a suitable supplier is one of the most important decisions in purchasing sector. It generally depends on various criteria. To effectively manage the strategically-important purchasing activity, suitable methods and criteria should be selected for the problem. This paper proposes a “data envelopment analysis with efficient and inefficient frontiers” approach to evaluate and select the best supplier in the presence of undesirable outputs and imprecise data. The data envelopment analysis with efficient and inefficient frontiers considers two types of efficiency for decision-making: One type is measured against the efficiency frontier and is called the best relative efficiency or the optimistic efficiency. The other one is measured against the inefficiency frontier and is called the worst relative efficiency or the pessimistic efficiency. In addition, by using this approach, new overall performance measures to score the suppliers in the presence of undesirable outputs and imprecise data is introduced. Compared to the traditional approach, data envelopment analysis with efficient and inefficient frontiers approach identifies the best supplier more easily and accurately. Two numerical examples illustrate the application of the proposed approach.

This paper presents a longitudinal study on manufacturing strategy clusters in two time periods with a six-year interval. In longitudinal study, data were collected from a representative sample in different times. To conduct a longitudinal study, two different types of clustering on the manufacturing strategies were used in factories of Iran in two time periods. For this purpose, the data of production factories at two time periods (years between 2009 and 2015) were used. Clustering validation was studied by using discriminate analysis, and then changes created in production targets of these clusters have been examined by using Euclidean distance, Multivariate Analysis of Variance and Variance Analysis. The results show that there are similarities and differences between clusters in two time periods.

In evaluating of organizations and institutions, one of the most important goals is to rank the units based on their performance. Since commonly used method of decision-making in data envelopment analysis may lead to several efficient units, selecting the best of all units is always one of the main challenges in data envelopment analysis. In this connection, different methods have been introduced for ranking units. In this paper, a new method called common weights has been studied in detail. Two techniques (common weight and TOPSIS) have been studied on the real data of 17 banks in Semnan province. The results indicate that both two methods have achieved perfect ratings. Comparing the two methods shows that the common weight rating is much closer to the reality. In addition, common weight is a non-parametric method and has received a better rating based on the efficiency (relative) of efficient units. In the suggested method (common weight), all decision-making units have been taken together, while in the TOPSIS model, it is not so.