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The main purpose of this paper is to propose a new approach to determine the project activities weight factors using data envelopment analysis. Afterward, the model is applied in Mobarkeh Steel Company as a case study. Accordingly, the project schedule and plans can be written on the basis of the gained weight factors.

This study proposed an approach to determine the weights of activities using Data Envelopment Analysis. This approach consists of four phases. In the first phase, project activities are extracted based on the work breakdown structure. In the second phase, the parameters affecting the importance of activities are determined through a review of the related literature and based on the experts' opinions. In the third phase, the proper data envelopment analysis model is chosen and the inputs and outputs are signified. Then, the activities' weights are determined based on the efficiency numbers. Finally, the model is solved for the case of Isfahan Mobarakeh Steel Company.

The proposed method aimed to calculate the project activities weight factor. Thus, influential parameters on project activities importance include activity duration, activity cost, activity importance which includes successors and predecessors, activity difficulty which includes skill related (education and experience), safety, communication rate, intellectual effort, physical effort, unfavorable work conditions and work related hazards, have been recognized. Then, Projects' data were extracted from the organizational expert's opinions and recorded data in documents. Thereupon, applying DEA, the activities weight factor were calculated based on the efficiency numbers. The results show that the model is applicable and has promising benefits in real-world problems.

Planning is one the most fundamental steps of project management. The ever-growing business environment demands for more complex projects with larger number of activities wants more efficient project managers. Organizational resources are limited; therefore, activities planning is a critical from the perspectives of both managers and researchers. Knowing the importance of the activities can help to manage activities more efficient and to allocate time, budget, cost and other resources more accurate. Different elements such as cost, time, complexity, and difficulty can affect the activity weight factor. In this study, the proposed approach aims to determine the weights of activities using Data Envelopment Analysis.

As far as the authors know, no research has already been carried out on the multi-floor dynamic facility layout problem (MF-DFLP) in the continuous form regarding the flexible bay structure, the number and the variable location of the elevator. Therefore, the present paper models the given problem and attempts to find a sub-optimal solution for it using a meta-heuristic simulated annealing (SA) algorithm.

The efficient use of resources has always been a prominent matter for decision-makers. Many reasons including land use, construction considerations and proximity of departments have led to the design of multi-floor facilities. On the other hand, their fast-evolving environment calls for dynamic planning. Therefore, in this paper, a model and the SA algorithm for MF-DFLP are presented.

After presenting a mathematical model, the problem was solved precisely in a small size using the GAMS software. Also, a near-optimal solution method using a SA meta-heuristic algorithm is suggested and the proposed algorithm was run in the MATLAB software. To evaluate the presented model and the proposed solution, some test cases were considered in two aspects. The first aspect was the test cases that are newly generated in small, medium and large sizes to compare the exact optimal solution with the results of the meta-heuristic algorithm. Eight test cases with small sizes were solved using the GAMS software, the optimum solutions were obtained in a reasonable time, and the cost of their solutions was equal to that of the SA algorithm. Eight test cases with medium sizes were run in the GAMS software with the time limit of 80,000 s, and the SA algorithm had performed better for these test cases. Two test cases were also considered in large size that GAMS could not solve them, whereas the SA algorithm successfully found a proper solution for each. The second aspect included the test cases from the literature. The result showed that suggested algorithm is more capable of finding best solutions than compared algorithms.

In this paper, an unequal area MF-DFLP was studied in a continuous layout form in which the location and number of the elevators were considered to be variable, and the layouts were considered with flexible bay structure. These conditions were investigated for the first time.

Adopting efficient marketing strategies is a challenging task in a competitive market place involving complex marketing planning, techniques and mechanisms to identify the best course of action under these circumstances and finding optimal solutions or stable outcomes. Decisions and strategies of competitors in the market influence the selection of the appropriate marketing strategy. The main purpose of this paper is to develop a mathematical methodology based on the game theory approach for planning optimal marketing-mix strategies in dynamic competitive markets, taking into account strategic foresight and interaction effects.

The game theory approach, as a decision-making tool in conflict situations, is suggested for planning and adopting optimal marketing strategy. The main intellectual attraction of the game theory is essentially a question of how to act in gaming situations against highly rational opponents A kind of static, finite and non-cooperative game analytics approach has been developed for this issue, and the proposed model has been implemented to design optimal marketing strategies for two top brands of the automotive parts market in Iran.

The findings of this study show that the optimal marketing-mix strategy for brand A is pricing and for brand B is the product strategy.

Game theory and the Nash equilibrium model can provide a practical approach to find and adopt the right strategy, know competitors' movements and strategies and get more profit.

The integration of the game theory approach into the marketing mix framework has been adopted as a generalized model for marketing strategy planning and analysis as well as to resolve some shortcomings of the marketing mix framework. The Nash equilibrium model has been used to analyze the results. The incorporation of game theory into marketing models has the potential to enrich the scope of marketing modeling.

The purpose of the study is to assess manufacturing firm performance indicators using a reasonably comprehensive integrated BSC-Game model to empirically determine the importance of the perspectives and indicators under evaluation and the best combination of indicators.

After identification of manufacturing indicators of the firm, the Shapley value index is used as the solution of the cooperative game to determine the importance of the perspectives and indicators under evaluation and the best combination of indicators to facilitate the achievement of target goals.

The game theory approach is used as a technique to rank BSC perspectives of the firm's manufacturing performance. The results reveal that the customers' perspective receives the highest ranking. The knowledge sharing, new technology, customer satisfaction and sale profitability are considered as the best combination of BSC indicators.

The integrated BSC-Game framework, approach and outcomes can be beneficial to practitioners and researchers who aim to select the proper indicators’ policy in manufacturing performance field.

This paper aims to propose an integrated centralized data envelopment analysis (CDEA)-balanced scorecard (BSC) model to provide a selective approach to determine the most efficient indicators for evaluating the four perspectives of the BSC.

An integer linear programming model based on the efficiency concept of the CDEA method is presented to select the best indicators for evaluating four perspectives of the BSC. The basis for selecting indicators in this method is to maximize the overall performance of each BSC perspective. The modeling is performed on a real case. The considered model is solved using a general algebraic modeling system software for the data set of the real case.

A real-world case is solved using the proposed method. The integration of the CDEA and the BSC seems to be advantageous because it sheds more light on the complexity and tradeoffs inherent in actual performance measurement. It is important to note that there cannot be a unique and universal model of performance measurement applicable in every situation, in every organization and at any time.

The data set of a single organization in the manufacturing industry is used to show the performance of the proposed mathematical model; therefore, generalization of the results should be done cautiously. This framework is based on the Iranian community and experts’ viewpoints; therefore, different results may be obtained if it is applied elsewhere, and the importance of perspectives and their indicators might show different results in other populations and other countries. In addition, because the data is collected in a specific period of time, the results cannot be extended to other periods of time.

The main contribution of this paper lies in the adaption of a new integrated CDEA-BSC model to performance measurement in the industrial sector that technology improves the ultimate results of performance measurement and provides wider opportunities for decision-makers. This paper aids managers and decision-makers to control the efficient indicators in perspectives.