Choose the Best Project Based on Simulation Optimization and Ant Colony Optimization Algorithm


Authors

Hamid Reza Feili - Faculty of Engineering, Department of Industrial Engineering, Islamic Azad University of Karaj, Iran. Alireza Farsi - MBA, PUMBA ( Pune University MBA), Pune, India Niloofar Nobahari - Student of MBE, Amirkabir University of Technology, Tehran, Iran.


Abstract

The process of planning, scheduling and economizing of new project is getting more difficult. Considering lack of raw materials, strict standards and tough competition, taking the right decision is not a simple task any more. In the process of globalization, only companies will be successful which are able to commercialize their dream with controlling effecting factors. Financial, operational and time bonded factors which sometimes follow accidental trends. Considering the probability behavior of this factors, benefiting from simulation approach to formulate the effect of these factors are one of the main solutions. Therefore under follow article we use simulation methodology to evaluate R and D projects, affected by accidental factors. Bearing in mind with more repeat we minimize the mistakes in project and get to the optimize answer. To evaluate the projects, a financial model is being presented, including sales quantity and price to calculate the profit. Total cost is being calculated based on unit cost. To find the best answer we repeat the model more than 800 times with the help of Ant colony optimization algorithms. To elaborate on model, we have studied an operational unit and will show the sensitivity and analysis of model. Later we will see the result with the help of diagrams.


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ISRP Style

Hamid Reza Feili, Alireza Farsi, Niloofar Nobahari, Choose the Best Project Based on Simulation Optimization and Ant Colony Optimization Algorithm, Journal of Mathematics and Computer Science, 7 (2013), no. 2, 101 - 111

AMA Style

Feili Hamid Reza, Farsi Alireza, Nobahari Niloofar, Choose the Best Project Based on Simulation Optimization and Ant Colony Optimization Algorithm. J Math Comput SCI-JM. (2013); 7(2):101 - 111

Chicago/Turabian Style

Feili, Hamid Reza, Farsi, Alireza, Nobahari, Niloofar. "Choose the Best Project Based on Simulation Optimization and Ant Colony Optimization Algorithm." Journal of Mathematics and Computer Science, 7, no. 2 (2013): 101 - 111


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