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Articles by Mahdi Nasereddin
Total Records ( 2 ) for Mahdi Nasereddin
  Mahdi Nasereddin and Mansooreh Mollaghasemi
  In this study the use of reverse simulation metamodels as a decision support tool is explored. In reverse simulation metamodeling the outputs of the simulation model (performance measures) are used as the inputs to the metamodel and the metamodel approximates the inputs of the simulation (controllable factors). The focus of this study is the choice of the experimental design (D-optimal or orthogonal arrays) used to generate the data set used to create the reverse simulation metamodel was investigated using 36 simulation scenarios with different degrees of complexity. It was found that neural network metamodels trained using an orthogonal training set performed better than those trained using a D-optimal training set.
  Mahdi Nasereddin
  The focus of this study is on resource constrained project scheduling with stochastic task durations. In the extensive research performed in project scheduling, little research has been done with projects that have stochastic activity durations. In this study, we explore combining two priority rule based heuristics (Longest Activity First (LAF) and Greatest Resource Demand (GRD) using weights assigned to each heuristic. The heuristics are then used to schedule the project activities. Genetic Algorithms (GA) are used to find the optimal weights on the heuristics. The GA search was compared to both random and interval searches. Two performance measures were used: average percent deviation from the best mean project duration found by the enumerative search and average percent deviation from the best variance found by the enumerative search. An experimental analysis was conducted to evaluate the performance of the three approaches. A full factorial design with 10 replications was used in this evaluation. It was found that the interval search performs better than the random search, which in turn performs better than the GA.
 
 
 
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