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Volume 23, Issue 2 (6-2012)
Abstract
The ever severe dynamic competitive environment has led to increasing complexity of strategic decision making in giant organizations. Strategy formulation is one of basic processes in achieving long range goals. Since, in ordinary methods considering all factors and their significance in accomplishing individual goals are almost impossible. Here, a new approach based on clustering method is proposed to assist the decision makers in formulating strategies. Having extracted the internal and external factors, after setting long range goals, the factor-goal matrices are generated according to the impact rate of factors on goals. According to created matrices, clusters including goals and factors are formed. By considering individual clusters the strategies are proposed according to the current state of clusters for the organization. By applying this new method the opportunity of considering the impact of all factors and its interactions on goals are not lost. Strategy-factor and strategy-goal matrices are utilized to validate the proposed method. To show the appropriateness and practicality of our approach, particularly in an environment with a large number of interacting goals and factors, we have implemented the approach in Mahmodabad Training Center (MTC) in Iran. The resulting goal-factor, current and dated states of clusters, also, strategy-goal and strategy-factor matrices for model validation and route branch indices for finding out how the organization achieved each goal are reported.
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Volume 23, Issue 2 (6-2012)
Abstract
Nowadays, project selection is a vital decision in many organizations. Because competition among research projects in order to gain more budgets and to attain new scientific domain has increased. Due to multiple objectives and budgeting restrictions for academic research projects have led to the use of expert system for decision making by academic and research centers. The existing methods suffer from deficiencies such as solution time inefficiency, ineffective assessment process, and unclear definition of appropriate criteria. In this paper, a fuzzy expert system is developed and improved for decision making in allocating budgets to research projects, by using the analytic network process(ANP). This has led to fewer rules and regulation, faster and more accurate decision-making, fewer calculations, and less system complexity. The rules of the expert system exacted in C# environment, consider all of the conditions and factors affecting the system. We describe the results of proposed model to measure its advantages and compare to existing selection processes for 120 projects. We also discuss the potential of proposed expert system in supporting decision making. The implementation results show that this system is significantly valid in selecting high-priority projects with respect to the known criteria , decision making regarding the determination of the assessment factors, budget allocation, and providing the appropriate initiatives for the improvement of the low-priority projects.
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Volume 23, Issue 2 (6-2012)
Abstract
The problem of staff scheduling at a truck hub for loading and stripping of the trucks is an important and difficult problem to optimize the labor efficiency and cost. The trucks enter the hub at different hours a day, in different known time schedules and operating hours. In this paper, we propose a goal programming to maximize the labor efficiency via minimizing the allocation cost. The proposed model of this paper is implemented for a real-world of a case study and the results are analyzed.
Mehdi Mahnam , Seyyed Mohammad Taghi Fatemi Ghomi ,
Volume 23, Issue 4 (11-2012)
Abstract
Fuzzy time series have been developed during the last decade to improve the forecast accuracy. Many algorithms have been applied in this approach of forecasting such as high order time invariant fuzzy time series. In this paper, we present a hybrid algorithm to deal with the forecasting problem based on time variant fuzzy time series and particle swarm optimization algorithm, as a highly efficient and a new evolutionary computation technique inspired by birds’ flight and communication behaviors. The proposed algorithm determines the length of each interval in the universe of discourse and degree of membership values, simultaneously. Two numerical data sets are selected to illustrate the proposed method and compare the forecasting accuracy with four fuzzy time series methods. The results indicate that the proposed algorithm satisfactorily competes well with similar approaches.
Mehdi Khashei , Farimah Mokhatab Rafiei, Mehdi Bijari ,
Volume 23, Issue 4 (11-2012)
Abstract
In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficient once in financial markets. In this paper, the performance of four interval time series models including autoregressive integrated moving average (ARIMA), fuzzy autoregressive integrated moving average (FARIMA), hybrid ANNs and fuzzy (FANN) and Improved FARIMA models are compared together. Empirical results of exchange rate forecasting indicate that the FANN model is more satisfactory than other those models. Therefore, it can be a suitable alternative model for interval forecasting of financial time series.
Navid Khademi, Afshin Shariat Mohaymany, Jalil Shahi, Mojtaba Rajabi,
Volume 24, Issue 3 (9-2013)
Abstract
Most of the researches in the domain of fuzzy number comparisons serve the fuzzy number ordering purpose. For making a comparison between two fuzzy numbers, beyond the determination of their order, it is needed to derive the magnitude of their order. In line with this idea, the concept of inequality is no longer crisp however it becomes fuzzy in the sense of representing partial belonging or degree of membership. In this paper we propose a method for capturing the membership degree of fuzzy inequalities through discretizing the μ-axis into equidistant intervals. It calculates m in the fuzzy inequalities ≤ m and ≥m among two normal fuzzy numbers. In this method, the two μ-axis based discretized fuzzy numbers are compared point by point and at each point the degree of preferences is identified. To show its validity, this method is examined against the essential properties of fuzzy number ordering methods in [Wang, X. and E.E. Kerre, Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets and Systems, 2001. 118(3): p. 375-385.] The result provides promising outcomes that may be useful in the domain fuzzy multi criteria or multi-attribute decision making analysis and also fuzzy mathematical programming with fuzzy inequality constraints.
Ashwin S. Chatpalliwar, Vishwas S. Deshpande, Jayant P. Modak, Nileshsingh V. Thakur,
Volume 24, Issue 3 (9-2013)
Abstract
This paper mainly focuses the study and analysis of the existing contributions related to the Biodiesel production. It, firstly, discuss the key issues related contributions which include chemical process, reactor designing, plantation, blending and applications. Next, it summarizes the analysis of the other prominent contributions related to process model, design, production, cost, optimization, feasibility, safety, effects, challenges and future of the Biodiesel. It also presents the discussion on the open issues in Biodiesel. Secondly, an approach is suggested for the design of the Biodiesel manufacturing plant in view of cost and capacity. The suggested approach is based on the mathematical model. This paper provides the brief study of Biodiesel production and plant design and it can be helpful to the beginners in the domain of renewable energy research.
Mohammadjafar Tarokh, Mahsa Esmaealigookeh,
Volume 24, Issue 4 (12-2013)
Abstract
Abstract
Customer Lifetime Value (CLV) is known as an important concept in marketing and management of organizations to increase the captured profitability. Total value that a customer produces during his/her lifetime is named customer lifetime value. The generated value can be calculated through different methods. Each method considers different parameters. Due to the industry, firm, business or product, the parameters of CLV may vary. Companies use CLV to segment customers, analyze churn probability, allocate resources or formulate strategies related to each segment. In this article we review most presented models of calculating CLV. The aim of this survey is to gather CLV formulations of past 3 decades, which include Net Present Value (NPV), Markov chain model, probability model, RFM, survival analysis and so on.
Nasim Nahavandi, Ebrahim Asadi Gangraj,
Volume 25, Issue 1 (2-2014)
Abstract
Flexible flow shop scheduling problem (FFS) with unrelated parallel machines contains sequencing in flow shop where, at any stage, there exists one or more processors. The objective consists of minimizing the maximum completion time. Because of NP-completeness of FFS problem, it is necessary to use heuristics method to address problems of moderate to large scale problem. Therefore, for assessment the quality of this heuristic, this paper develop a global lower bound on FFS makespan problems with unrelated parallel machines.
Amin Parvaneh, Mohammadjafar Tarokh, Hossein Abbasimehr,
Volume 25, Issue 3 (7-2014)
Abstract
Data mining is a powerful tool for firms to extract knowledge from their customers’ transaction data. One of the useful applications of data mining is segmentation. Segmentation is an effective tool for managers to make right marketing strategies for right customer segments. In this study we have segmented retailers of a hygienic manufacture. Nowadays all manufactures do understand that for staying in the competitive market, they should set up an effective relationship with their retailers. We have proposed a LRFMP (relationship Length, Recency, Frequency, Monetary, and Potential) model for retailer segmentation. Ten retailer clusters have been obtained by applying K-means algorithm with K-optimum according Davies-Bouldin index on LRFMP variables. We have analyzed obtained clusters by weighted sum of LRFMP values, which the weight of each variable calculated by Analytic Hierarchy Process (AHP) technique. In addition we have analyzed each cluster in order to formulate segment-specific marketing actions for retailers. The results of this research can help marketing managers to gain deep insights about retailers.
Mahdi Karbasian, Marziye Kashani, Bijhan Khayambashi, Mohsen Cheshmberah,
Volume 27, Issue 2 (6-2016)
Abstract
In this research we have presented a local model for implementing systems engineering activities in optimized acquisition of electronic systems in Electronic High-Tech Industrial. In this regard, after reviewing the literature and the use of documents, articles and Latin books, we have collected system acquisition life cycle models from different resources. after considering the criteria of the mentioned industry, we have designed two questionnaires and distributed them among some experts of industry and university. The Population studied here were all of the specialists of mentioned industry and our sample consist of 17 experts in this field. As the main focus of this research is on experts’ opinions, we used purposive sampling. Finally, we present local model using the results of the questionnaires and considering the standards, requirements and system engineering processes during system acquisition stages and then match them with our case study. this research includes some innovations such as: flexibility of model under different conditions, choosing the appropriate positions for applying systems engineering reviews, and also the use of foresight issue in the initial phase of model, which have been neglected in other presented models in previous researches.
Roghaye Hemmatjou, Nasim Nahavandi, Behzad Moshiri,
Volume 27, Issue 3 (9-2016)
Abstract
In most of the multi–criteria decision–analysis (MCDA) problems in which the Choquet integral is used as aggregation function, the coefficients of Choquet integral (capacity) are not known in advance. Actually, they could be calculated by capacity definition methods. In these methods, the preference information of decision maker (DM) is used to constitute a possible solution space. The methods which are based on optimizing an objective function most often suffer from three drawbacks. Firstly, the selection of the ultimate solution from solution set is arbitrarily done. Secondly, the solution may provide more information than whatever proposed by DM. Thirdly, DM may not fully interpret the results. Robust capacity definition methods are proposed to overcome these kinds of drawbacks, on the other hand these methods do not consider evenness (uniformity) which is a major property of capacity. Since in capacity definition methods, the preference information on only a subset of alternatives called reference alternatives, is used, defining the capacity as uniform as possible could improve its capability in evaluating non–reference alternatives. This paper proposes an algorithm to define a capacity that is based only on the preference information of DM and consequently is representative. Furthermore, it improves evenness of capacity and consequently its reliability in evaluating non–reference alternatives. The algorithm is used to evaluate power plant projects. Power plant projects are of the most important national projects in Iran and a major portion of national capital is invested on them, so these projects should be scientifically evaluated in order to figure out their performance. Case–specific criteria are considered in addition to general criteria used in project performance evaluation. The evaluation results obtained from proposed algorithm are compared with those of the most representative utility function method.
Hooman Abdollahi, Seyed Babak Ebrahimi, Ali Farmani,
Volume 27, Issue 3 (9-2016)
Abstract
Presently, emerging economies are acquiring singular positions all over the world. The complexities of nowadays economy have caused international companies and investors to be of a tendency towards emerging markets for more profitability and growth. This study aims to find the relationships between firm's profitability and growth in Iranian manufacturing industry consisting of Tehran Stock Market listed manufacturing firms covering 2005-2014. In order to understand the direction of causality between firm growth and profitability, we use system-GMM (Generalized Method of Moments) to estimate growth and profit regressions. The results obtained indicate that there is positively bilateral relationship between profitability and growth in the case of Iranian manufacturing firms. Also, we find the positive impact of current profit (growth) on current growth (profit) is stronger than the impact of the prior year.
Ghasem Moslehi, Omolbanin Mashkani,
Volume 29, Issue 1 (3-2018)
Abstract
In single machine scheduling problems with availability constraints, machines are not available for one or more periods of time. In this paper, we consider a single machine scheduling problem with flexible and periodic availability constraints. In this problem, the maximum continuous working time for each machine increases in a stepwise manner with two different values allowed. Also, the duration of unavailability for each period depends on the maximum continuous working time of the machine in that same period, again with two different values allowed. The objective is to minimize the number of tardy jobs. In the first stage, the complexity of the problem is investigated and a binary integer programming model, a heuristic algorithm and a branch-and-bound algorithm are proposed in a second stage. Computational results of solving 1680 sample problems indicate that the branch-and-bound algorithm is capable of not only solving problems of up to 20 jobs but also of optimally solving 94.76% of the total number of problems. Based on numerical results obtained, a mean average error of 2% is obtained for the heuristic algorithm.
Mojtaba Hamid, Mahdi Hamid, Mohammad Mahdi Nasiri, Mahdi Ebrahimnia,
Volume 29, Issue 2 (6-2018)
Abstract
Surgical theater is one of the most expensive hospital sources that a high percentage of hospital admissions are related to it. Therefore, efficient planning and scheduling of the operating rooms (ORs) is necessary to improve the efficiency of any healthcare system. Therefore, in this paper, the weekly OR planning and scheduling problem is addressed to minimize the waiting time of elective patients, overutilization and underutilization costs of ORs and the total completion time of surgeries. We take into account the available hours of ORs and the surgeons, legal constraints and job qualification of surgeons, and priority of patients in the model. A real-life example is provided to demonstrate the effectiveness and applicability of the model and is solved using ε-constraint method in GAMS software. Then, data envelopment analysis (DEA) is employed to obtain the best solution among the Pareto solutions obtained by ε-constraint method. Finally, the best Pareto solution is compared to the schedule used in the hospitals. The results indicate the best Pareto solution outperforms the schedule offered by the OR director.
Bahareh Vaisi, Hiwa Farughi, Sadigh Raissi,
Volume 29, Issue 3 (9-2018)
Abstract
This paper focused on scheduling problems arising in a two-machine, identical parts robotic cell configured in a flow shop. Through current research, a mathematical programming model on minimizing cycle time as well operational cost, considering availability of robotic cell as a constraint, is proposed to search for the optimum allocation and schedule of operations to these two machines. Two solution procedures, including weighted sum method and ∊-constraint method are provided. Based on the weighted sum method, like some previous studies, sensitivity analysis on model parameters were done and the optimum solutions were compared with previous results, while the ∊-constraint method can find the Pareto optimal solutions for problems with up to 18 operations in a reasonable time.
Hassan Rashidi, Fereshteh Azadi Parand,
Volume 30, Issue 3 (9-2019)
Abstract
One of the modern paradigms to develop a system is object oriented analysis and design. In this paradigm, there are several objects and each object plays some specific roles. There is a sequence of activities to develop an analysis model. In the first step, we work in developing an initial use case model. Then in the second step, they identify a number of concepts and build a glossary of participating objects. Identifying attributes of objects (and classes) is one of the most important steps in the object-oriented paradigm. This paper proposes a method to identify attributes of objects and verify them. The method is also concerned itself with classifying and eliminating the incorrect attributes of objects. Then the method is evaluated in a large application, a Control Command Police System. After that, several guidelines on attributes of objects, based on the practical experience obtained from the evaluation, are provided.
Maryam Shekary Ashkezary, Amir Albadavi, Mina Shekari Ashkezari,
Volume 30, Issue 4 (12-2019)
Abstract
One of the key issues in the studies on customer relationship management (CRM) and modalities of marketing budget allocation is to calculate the customer’s lifetime value and applying it to macro-management decisions. A major challenge in this sector pertains to making calculations so as to incorporate the possibility of changes in the behavior of customers with the turn of time in the model.
In this article, we first classify the customers of ISACO using clustering techniques and use multilayer neural network to calculate the monetary value of each group of customers during the specific period of time. Then, we use the Markov chain approach to develop a model for calculating the lifetime value of ISACO’s customers by taking into consideration the possibility of changes in their behavior in future time periods.
In this study, a new approach has been used to estimate the parameters of the model proposed for calculating the future lifetime value of ISACO’s customers. This method takes into consideration the possibility of changes in the customer behavior throughout their interaction with the company.
The results obtained here may be used in the allocation of marketing budget and adoption of macro-management decisions to envisage various projects for customers with different lifetime value.
Tahere Hashemi, Ebrahim Teimoury, Farnaz Barzinpour,
Volume 31, Issue 3 (9-2020)
Abstract
Retailers selling fresh products often encounter unsold inventory remains at the end of each period. The leftover product has a lower perceived quality than the new product. Therefore, retailers try to influence consumers’ preferences through price differentiation that leads to an internal competition based on product age and prices. This paper addresses the pricing and inventory control problem for fresh products to capture the influence of this competition on the supply chain members’ decisions and profits. A new coordination model based on a return policy with the revenue and cost-sharing contract is developed to improve the profits of independent supply chain members. The supply chain consists of one supplier and one retailer, where consumers are sensitive to the product’s retail price and freshness degree. Firstly, the retailer’s optimal decisions are derived in a decentralized decision-making structure. Then a centralized approach is used to optimize the supply chain decisions from the whole supply chain viewpoint. Eventually, a new coordination contract is designed to convince the members to participate in the coordination model. Numerical examples are carried out to compare the performance of different decision-making approaches. Our findings indicate that the proposed contract can coordinate the supply chain effectively. Furthermore, the coordinated decision-making model is more profitable and beneficial for the whole supply chain compared to the decentralized one. The results also demonstrate that when consumers are more sensitive to freshness, the simultaneous sale of multiple-aged products at different prices is more profitable.
I Shostak, Mariia Danova, R Melnyk, O Melnyk,
Volume 31, Issue 4 (11-2020)
Abstract
A research was conducted to form an approach to the design and implementation of a multi-agent control system of smart elements for a “Smart house”. The system was built on the example of three intelligent robots. In the architecture of the system under development, the main part is the subject-independent multi-agent kernel, which includes the following basic components: direct access service, the messaging service, agent class library, agent community, ontology. It was found that the multi-agent approach using ontologies in the framework of this problem significantly exceeds traditional methods in efficiency. The experimental part includes a description of scenarios for organizing the functioning of smart elements in a multi-agent system. This system simulates the adaptive, remote and almost independent functioning of the intelligent objects of the “Smart House”. The developed scenarios have shown the feasibility of applying this approach for a wide class of objects, such as a "Smart house".
