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Journal of Decisions and Operations Research aihe
  • Publication Office:
    Ayandegan Institute of Higher Education, Tonekabon, Iran
    P.O. Box: 46818-53617, Tonekabon, Mazandaran, Iran
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In managing a project, reliable prediction is an essential element for success. Project managers are always looking for controlling their projects to make sure the the project is within acceptable limits. For a long time, the earned value... more
In managing a project, reliable prediction is an essential element for success. Project managers are always looking for controlling their projects to make sure the the project is within acceptable limits. For a long time, the earned value management (EVM) for pursuing time performance and the cost of the project has been used. However, using this method to valuate project time performance by utilizing the time performance index (SPI) by researchers and practitioners has been faced with serious criticism. Therefore, the present study proposes a framework for assessment and prediction of the temporal performance of each of the thread activities in project management. In this framework, using the multi objective league championship algorithm (MOLCA), the initial plan of the projects is optimized and then via using the Kalman Filter prediction method, project execution planning is done such that the projects in conditions of uncertainty could be forecasted and ahead horizon being demonstrated accurately with the least error for project managers. In this paper, in order to ensure the quality of the solutions, the output of the algorithm is compared with genetic algorithms (NSGII) and particle swarm optimization (MOPSO), where results demonstrate the superiority of the proposed algorithm.
Since much of human reasoning is based on imprecise, vague and subjective values, most of decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Ranking fuzzy numbers is one of very important research... more
Since much of human reasoning is based on imprecise, vague and subjective values, most of decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Ranking fuzzy numbers is one of very important research topics in fuzzy set theory because it is a base of decision-making in applications. Although so far, many methods for ranking of fuzzy numbers have been discussed broadly, most of them contained some shortcomings, such as requirement of complicated calculations, inconstancy with human intuition and indiscrimination. In this paper, we introduce a new method by using of the affine combination on the circumcenter. This method ranks various types of fuzzy numbers which include normal, generalized trapezoidal, and triangular fuzzy numbers along with crisp numbers with the particularity that crisp numbers are to be considered particular cases of fuzzy numbers. The advantages of the new proposed are that it can be applied for most of the defuzzification and the calculation is far simple and easy than previous methods. The effectiveness of the proposed method and its advantages is demonstrated by numerical examples, comprehensive comparing different ranking method with this method and also its benefits will be illustrated by the numerical example, as well as a case study on supply chain management.
Quality loss function is common techniques in robust design terminology that consider the deviation of output from ideal point and variability as well. Mostly in practice, processes are affected by external uncontrollable factors that... more
Quality loss function is common techniques in robust design terminology that consider the deviation of output from ideal point and variability as well. Mostly in practice, processes are affected by external uncontrollable factors that causes output of process to be far from ideal points with variability around its exact value. In this research, the common Taguchi quality loss function is applied to propose a new robust optimization model that able to choice optimal results of input variables. In this model, the quality loss function is expanded and a nonlinear optimization model is introduced in order to minimize the effect of environmental noise variables. At the end, a numerical example is presented to show the applicability of the proposed model for investigating the best levels of input variables in noisy process.
‌In today’s highly competitive business environment, which is known by characteristics of low profitability, high customer expectations for high-quality products and minimum waiting time, make companies efforts to transform constraints... more
‌In today’s highly competitive business environment, which is known by characteristics of low profitability, high customer expectations for high-quality products and minimum waiting time, make companies efforts to transform constraints into opportunities for gaining competitive advantage by optimizing their business processes. In such a situation, appropriate supplier selection can play a key role in the efficiency and effectiveness of the organization and have a direct impact on reducing costs, profitability, and flexibility of a company. The purpose of this research is to provide a supplier selection model with simultaneous consideration of two sources of inventory control and pricing in the supply chain. To assess the validity and reliability of the model, the actual data of the Seven Diamond Industries Company including input materials (Hot Roll) and products (galvanized sheets) have been used. The proposed model is coded in the GAMS software and its results have been analyzed.