Estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. This estimation has amajor impact on the success of construction projects. Indeed, this estimation supports the required information that can be emp More
Estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. This estimation has amajor impact on the success of construction projects. Indeed, this estimation supports the required information that can be employed in costmanagement and budgeting of these projects. The purpose of this paper is to introduce an intelligent model to improve the conceptual costaccuracy during the early phases of the life cycle of projects in construction industry. A computationally efficient model, namely supportvector machine model, is developed to estimate the conceptual costs of construction projects. The proposed neural network model is trainedby a cross validation technique in order to produce the reliable estimations. To demonstrate the performance of the proposed model, twopowerful intelligent techniques, namely nonlinear regression and back-propagation neural networks (BPNNs), are provided. Their resultsare compared on the basis of the available dataset from the related literature in construction industry. The computational results illustratethat the presented intelligent model performs better than the other two powerful techniques.
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In this paper, we study different methods of solving joint redundancy-availability optimization for series-parallel systems with multi-state components. We analyzed various effective factors on system availability in order to determine the optimum number and version of More
In this paper, we study different methods of solving joint redundancy-availability optimization for series-parallel systems with multi-state components. We analyzed various effective factors on system availability in order to determine the optimum number and version of components in each sub-system and consider the effects of improving failure rates of each component in each sub-system and improving reliability of each sub-system. The target is to determine optimum values of all variables for improving the availability level and decreasing the total cost of the system. At first, the exact values of variables are determined using a mathematical model; then, the results of SA-Parallel, VDO-Parallel and genetic algorithms are compared with the exact solution.
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Task assignment problem (TAP) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints.
TAP is a More
Task assignment problem (TAP) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints.
TAP is a combinatorial optimization problem and NP-complete. This paper proposes a hybrid meta-heuristic algorithm for solving TAP in a heterogeneous distributed computing system. To compare our algorithm with previous ones, an extensive computational study on some benchmark problems was conducted. The results obtained from the computational study indicate that the proposed algorithm is a viable and effective approach for the TAP.
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Considering the increasingly high attention to quality, promoting the reliability of products during designing process has gained significant importance. In this study, we consider one of the current models of the reliability science and propose a non-linear programming More
Considering the increasingly high attention to quality, promoting the reliability of products during designing process has gained significant importance. In this study, we consider one of the current models of the reliability science and propose a non-linear programming model for redundancy allocation in the series-parallel systems according to the redundancy strategy and considering the assumption that the failure rate depends on the number of the active elements. The purpose of this model is to maximize the reliability of the system. Internal connection costs, which are the most common costs in electronic systems, are used in this model in order to reach the real-world conditions. To get the results from this model, we used meta-heuristic algorithms such as genetic algorithm and simulation annealing after optimizing their operators’ rates by using response surface methodology.
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