Back-propagation Neural Network (BPNN) algorithm is one of the most widely used and a popular technique to optimize the feed forward neural network training. Traditional BP algorithm has some drawbacks, such as getting stuck easily in local minima and slow speed of convergence. Nature inspired meta-heuristic algorithms provide derivative-free solution to optimize complex problems. This paper pr...

In this paper simulated annealing and genetic algorithms are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuristics, is ...

Charge-transfer rate constants (kCT) are required for the design of fullerene-based solar cells. We have assessed performance six long-range corrected hybrid functionals and a meta-hybrid-GGA functional calculation kCT with Marcus equation.

The ground and lower excited states of Fe2, Fe2(-), and FeO(+) were studied using a number of density functional theory (DFT) methods. Specific attention was paid to the relative state energies, the internuclear distances (re), and the harmonic vibrational frequencies (ωe). A number of factors influencing the calculated values of these properties were examined. These include basis sets, the nat...

The range-separated hybrid density functionals are very successful in describing a wide range of molecular and solid-state properties accurately. In principle, such functionals are designed from spherically averaged or system averaged as well as reverse engineered exchange holes. In the present attempt, the screened range-separated hybrid functional scheme has been applied to the meta-GGA rung ...

production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...

in this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. in this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. to tackle the problem efficiently and effectively, an effici...

in this paper, the distribution network for multi-level supply chain has been studied. products produced in factories are sent to customers through warehouses and distribution centers based on specific demands. warehouses as holding inventory facilities are located close to factories and the distribution centers are placed in the most accessible locations for services near customers. each item ...

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the present study is concerned with the simultaneous optimization of the size of components and the arrangement of connections for performance-based seismic design of low-rise spsws. design variables include the size of beams and columns, the thickness of the infill panels, the type of each beam-to-column connection and the type of each infill-to-boundary frame connection. the objective functio...