A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

Abstract Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization. In this article, first, a stochastic programming model with uniform distribution assumption is developed for refinery production planning under demand uncertainty, and then a hybrid programming model incorporating the linear programming model with the stochastic programming one by a weight factor is proposed. Subsequently, piecewise linear approximation functions are derived and applied to solve the hybrid programming model-under uniform distribution assumption. Case studies show that the linear approximation algorithm is effective to solve.the hybrid programming model, along with an error≤0.5% when the deviatiorgmean≤20%. The simulation results indicate that the hybrid programming model with an appropriate weight factor （0.1-0.2） can effectively improve the optimal operational strategies under demand uncertainty, achieving higher profit than the linear programming model and the stochastic programming one with about 1.3% and 0.4% enhancement, respectavely.

Application of Hybrid Programming with Matlab and C # in Reliability Analysis Software

Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis software efficiency and accuracy significantly.Procedures of hybrid programming with Matlab and C# in reliability analysis software are introduced in this paper.Finally a mathematical problem is tested to verify the feasibility of this programming method.

Setup and application of a structural seismic hybrid simulation system on local area network

To implement structural hybrid simulation independent of the control system of any testing equipment in civil engineering, an external command control approach is put forward. Several setup technologies and the corresponding API approaches are investigated to simultaneously combine numerical simulation with physical testing. Hybrid program technology is put forward and described in detail, using Visual C++ program to effectively and accurately control testing equipment and MATLAB program to implement numerical simulation with easy extension. The control program of testing equipment and numerical simulation program are integrated by calling MATLAB engine in Visual C++. A hybrid simulation about a full-scale six-story masonry structure is carried out. The testing results manifest that the external command control approach has the versatility because of simple hardware connection and control program independent on control software of testing equipment; powerful program function of Visual C++ and flexible program of MATLAB are integrated by hybrid program technology; hybrid simulation system provides a realistic and cost-effective testing platform that enables earthquake engineer researchers to accurately and efficiently capture the seismic performance of large or complex structures without having to carry out physical testing of the entire structure.

Instantaneous rotation speed measurement and error analysis for variable speed hydraulic system

In order to monitor the working state of piston motor and measure its instantaneous rotation speed accurately, the measuring principle and method of instantaneous rotation speed based on industrial personal computer and data acquisition card are introduced, and the major error source, influence mechanism and processing method of data quantization error are dis- cussed. By means of hybrid programming approach of LabVIEW and MATLAB, the instantaneous rotation speed measurement system for the piston motor in variable speed hydraulic system is designed. The simulation and experimental results show that the designed instantaneous speed measurement system is feasible. Furthermore, the sampling frequency has an important influ- ence on the instantaneous rotation speed measurement of piston motor and higher sampling frequency can lower quantization er- ror and improve measurement accuracy.

High performance computing for flood simulation using Telemac based on hybrid MPI/OpenMP parallel programming

Usually simulations on environment flood issues will face the scalability problem of large scale parallel computing.The plain parallel technique based on pure MPI is difficult to have a good scalability due to the large number of domain partitioning.Therefore,the hybrid programming using MPI and OpenMP is introduced to deal with the issue of scalability.This kind of parallel technique can give a full play to the strengths of MPI and OpenMP.During the parallel computing,OpenMP is employed by its efficient fine grain parallel computing and MPI is used to perform the coarse grain parallel domain partitioning for data communications.Through the tests,the hybrid MPI/OpenMP parallel programming was used to renovate the finite element solvers in the BIEF library of Telemac.It was found that the hybrid programming is able to provide helps for Telemac to deal with the scalability issue.

Parallelization and Acceleration of Dynamic Option Pricing Models on GPU-CPU Heterogeneous Systems

In this paper,stochastic global optimization algorithms,specifically,genetic algorithm and simulated annealing are used for the problem of calibrating the dynamic option pricing model under stochastic volatility to market prices by adopting a hybrid programming approach.The performance of this dynamic option pricing model under the obtained optimal parameters is also discussed.To enhance the model throughput and reduce latency,a heterogeneous hybrid programming approach on GPU was adopted which emphasized a data-parallel implementation of the dynamic option pricing model on a GPU-based system.Kernel offloading to the GPU of the compute-intensive segments of the pricing algorithms was done in OpenCL.The GPU approach was found to significantly reduce latency by an optimum of 541 times faster than a parallel implementation approach on the CPU,reducing the computation time from 46.24 minutes to 5.12 seconds.