Nasser Shahsavari-Pour; Hosein Kazemi; Morteza Hoseinzadeh; Daryoosh Maheri; shahla heydarbeigi
Abstract
Nowadays, one of the basic problems of organizations, in establishing the system of performance evaluation, is to identify the key indicators. In recent years, among the valuation models and performance, it has been more attention to the balanced scorecard; but many of the balanced assessment projects ...
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Nowadays, one of the basic problems of organizations, in establishing the system of performance evaluation, is to identify the key indicators. In recent years, among the valuation models and performance, it has been more attention to the balanced scorecard; but many of the balanced assessment projects face up to fail in action. The most important reasons behind the failure in the establishment of a weak balanced assessment is in the selection of the appropriate key indicators. Hence, this study tried to applying an appropriate method for providing a model for the selection of the performance appropriate key indicators by the help of the modified balanced scorecard model and the use of a linear programming and the Operating consequences of this approach will present as a case at Commercial Company in Kerman. This study is an applied research, its method is descriptive – analytic one. The population included 71 members of the technical staff of projects and storage installations of state Commercial Company in Kerman that 10 members were the managers of the company.
Mohammad Mahdi Bahrololoum; Mirfeiz Fallahshams; Ghasem Blue
Volume 13, Issue 39 , January 2016, , Pages 91-114
Abstract
In this study, the strategy of effective asset allocation under uncertainty with the capability of risk control, transaction cost reduction and favorable return realization is investigated. In order to implement this strategy and to overcome the shortfalls of classic portfolio optimization models in ...
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In this study, the strategy of effective asset allocation under uncertainty with the capability of risk control, transaction cost reduction and favorable return realization is investigated. In order to implement this strategy and to overcome the shortfalls of classic portfolio optimization models in dealing with uncertainty, the formation of an index fund using a robust approach and considering cardinality constraint became the agenda. Accordingly, in order to solve the index tracking problem, a linear programming model as minimizing the absolute deviation between the expected return of the index fund and that of the benchmark is presented. Considering the dimension of the solution space, a Meta heuristic genetic algorithm was implemented to solve the robust counterpart of the problem. The results of the analysis imply on the selection of 20 stocks as the index fund composition and indicate good performance of the index tracking funds based on criteria such as correlation, root mean square error and the excess return using out of sample data.
Payam Chiniforooshan; Behrooz Pourghannad; Narges Shahraki
Volume 9, Issue 23 , December 2011, , Pages 209-231
Abstract
In this paper, a mathematical model is proposed to solve cell formation problem considering alternative process routings in which more than one process route for each part can be selected. The model attempts to minimize intercellular movements and incorporates several real-life production factors and ...
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In this paper, a mathematical model is proposed to solve cell formation problem considering alternative process routings in which more than one process route for each part can be selected. The model attempts to minimize intercellular movements and incorporates several real-life production factors and practical constraints. In order to increase the flexibility provided by the multiplicity of routings, the model distributes production volume of each part among alternative routes. Also, a constraint enforcing work load balancing among machines is included in the model. Due to the complexity and combinatorial nature of this model, an enhanced algorithm comprised of a genetic algorithm and a linear programming is proposed for solving the model. The proposed algorithm is tested by a range of test problems and compared with two algorithms from the literature .The computational results show that the proposed algorithm is effective and the proposed approach offers better solution.
