modeling and simulation
Mohsen JavidMoayed; عباس Toloei Eshlaghy; Mohammad Ali Afshar kazemi
Abstract
Nowadays, more successful businesses are those that keep their customers satisfied and in addition to the macro level of their policies, also pay serious attention to the micro level and details of the market. In this article, in order to study the influential factors in the mobile phone market, the ...
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Nowadays, more successful businesses are those that keep their customers satisfied and in addition to the macro level of their policies, also pay serious attention to the micro level and details of the market. In this article, in order to study the influential factors in the mobile phone market, the dynamic system method with the discrete event method has been used in combination.In this paper, the first two mobile companies Hamrahe Aval and Irancell as the basic players in the Iranian mobile phone market are considered as two rivals. Since in recognizing and analyzing the influential factors on market share, operational and strategic levels affect each other, after specifying the impressive factors at each level, from the discrete event approach at the operational level, and the dynamic system approach at the strategic level and their combination has been used to indicate a compound model of the mobile phone market.Based on findings any change in the operational and strategic levels of each competitor will have a serious influence on the rate of increase / reduce of willingness on their services and the consequently increase or decrease in customers. On the other hand, it indicates how a more specified level of detail can be noticed by combining discrete event simulation methods and a dynamic system.In comparison the suggested combined model investigates more details of events than simple simulation models, so, it can be used to examine different ways for decision-making.
seyed mohammad ali khatami firouzabadi; seyed hossein galali; seyed ali mohammad parvardeh
Volume 11, Issue 29 , July 2013, , Pages 113-137
Abstract
The main purpose of this practical survey is devoted to identify the obstacles of strategic plan implementation among energy sector's contractors and then, to present a classification of identified obstacles on the basis of their priorities. In order to achieve this purpose, 8 factors were chosen as ...
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The main purpose of this practical survey is devoted to identify the obstacles of strategic plan implementation among energy sector's contractors and then, to present a classification of identified obstacles on the basis of their priorities. In order to achieve this purpose, 8 factors were chosen as the obstacles of strategic plans in energy sector following the literature review and experts comments, and then applied to 87 managers and senior experts of strategic planning in contracting firms by a questionnaire. The Fuzzy TOPSIS technique is assumed as a well-known Multiple-criteria Decision Making (MCDM) approach. Results showed that organizational structure was received the most priority as an obstacle in implementing strategic plan in contracting industry and operational planning, resource allocation, quality of strategy, communication, strategy executors, control and commitment got subsequent ranks. So, findings of this survey could improve the efficiency of contracting firm's managers to direct the process of strategy implementation and to overcome on identified obstacles
Amir Daneshvar; Mostafa Zandieh; Jamshid Nazemi
Volume 13, Issue 39 , January 2016, , Pages 1-34
Abstract
Outranking based models as one of the most important multicriteria decision methods need the definition of large amount of preferential information called “parameters” from decision maker. Because of the multiplicity of parameters, their confusing interpretation in problem context and the ...
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Outranking based models as one of the most important multicriteria decision methods need the definition of large amount of preferential information called “parameters” from decision maker. Because of the multiplicity of parameters, their confusing interpretation in problem context and the imprecise nature of data, Obtaining all these parameters simultaneously specially in large scale realistic credit problems which requires real time decision making is very complex and time-consuming.Preference Disaggregation approach infers these parameters from the holistic judgements provided by decision maker. This approach within multicriteria decision methods is equivalent to machine learning in artificial intelligence discipline.Under this approach this paper proposes a new learning method in which Genetic Algorithm(GA) in an evolutionary process induces all , ELECTRE TRI model parameters from training set then at the end of this process, classification is done on testing set by inferred parameters. Experimental analysis on credit data shows high quality and competitive results compared with some standard classification methods.
Omid Amirtaheri; Mostafa Zandieh; Behrouz Dorri
Abstract
In this paper, we investigate a decentralized manufacturer-distributer supply chain. In addition to global advertisement, the manufacturer participates in the local advertising expenditures of distributer. Bi-level programming approach is applied to model the relationship between the manufacturer and ...
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In this paper, we investigate a decentralized manufacturer-distributer supply chain. In addition to global advertisement, the manufacturer participates in the local advertising expenditures of distributer. Bi-level programming approach is applied to model the relationship between the manufacturer and retailer under two power scenarios of stackelberg game framework and the optimal policies in pricing, advertising, inventory management and logistics are identified. Two hierarchical genetic algorithms are proposed to solve the bi-level programming models. Based on collected data from Iranian automotive spare parts aftermarket, several numerical experiments are carried out to evaluate the validity of proposed models as well as the efficiency and effectiveness of solution procedures.
Samira Parsaiyan; Maghsoud Amiri; Parham Azimi; Mohammad Taghi Taghavifard
Abstract
The increasing concern about the deteriorating effects of supply chains related activities on the environment has led to the growing attention to develop green closed-loop supply chains in order to minimize greenhouse gases emission. This paper presents a green closed-loop supply chain model developed ...
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The increasing concern about the deteriorating effects of supply chains related activities on the environment has led to the growing attention to develop green closed-loop supply chains in order to minimize greenhouse gases emission. This paper presents a green closed-loop supply chain model developed under the demand uncertainty aiming at minimizing total cost and total CO2 emission across the supply chain, and maximizing the product’s market share in the presence of a competitor. In this regards, an agent-based market model is developed to estimate the demand’s parameter function then a hybrid simulation model which integrates agent-based and discrete event simulation modelling approaches is designed to simulate the closed-loop supply chain which is the novelty of this paper. Then, scenarios are created using Taguchi design of experiments (DOE) method, and are executed with the market model and the supply chain model to capture total cost, total CO2 and market share. A decision matrix is configured using scenarios and recorded results for three mentioned criteria and ELECTRE and SAW methods are used to rank scenarios and select the best one. The other contribution of this research is its comprehensiveness in considering variables related to three categories of inventory replenishment policy, marketing mix (price and advertisement) and transportation. An automotive industry case is provided to demonstrate the capabilities of the model and its applicability and effectiveness in resolving real-world problems.
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