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Tan Y.-Y.,Northeastern University China | Song J.-H.,Shanghai Baosight Software Co. | Liu S.-X.,Northeastern University China
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | Year: 2011

Reheating furnace is the major equipment in the hot-rolled production. Improving the scheduling of reheating furnace is an effective way to reduce the energy consumption and production costs. According to the production process and constraints on the reheating furnace, we propose a mathematical model for scheduling the reheating furnace, and present a scatter search(SS) algorithm to solve this model. We also design the random-variable-sequence-based voting combination operator(RVSBVCO) and the one-point-crossover combination operator(OPCCO). From the production data of an iron-and-steel production enterprise, we randomly generate 40 instances for testing the model and the algorithm. The impact on the effectiveness and efficiency of the algorithm from the sizes of reference sets and two combination operators is evaluated and compared with the results obtained from the genetic local search(GLS) algorithm. Results show that the proposed model and algorithm are effective for solving the reheating furnace scheduling problem. Source

Liu S.-X.,Northeastern University China | Song J.-H.,Shanghai Baosight Software Co.
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | Year: 2011

Combining constraint programming(CP) and mathematical programming(MP) to solve scheduling problems has been an interesting topic for researchers, and promising results are obtained. We propose a preprocessing approach for solving resource-constrained project-scheduling problems(RCPSP) with integer programming(IP) model, and prove an effective inequality theory for the IP model. The effective inequality can be obtained by solving a maximum clique problem which is built on a sub-network of the original project. A detailed computational experiment is performed using the well-known standard instances in PSPLIB. Computational results show that the proposed effective inequality remarkably improves the performances of the IP model. Finally, the computational results are analyzed and future research directions are discussed. Source

Zhang M.,Shanghai Baosight Software Co.
International Journal of Intelligent Computing and Cybernetics | Year: 2011

Purpose: A novel sexual adaptive genetic algorithm (AGA) based on Baldwin effect for global optimization is proposed to overcome the shortcomings of traditional GAs, such as premature convergence, stochastic roaming, and poor capabilities in local exploring. This paper seeks to discuss the issues. Design/methodology/approach: The proposed algorithm simulates sexual reproduction and adopts an effective gender determination method to divide the population into two subgroups of different genders. Based on the competition, cooperation, and innate differences between two gender subgroups, the proposed algorithm adjusts adaptively sexual genetic operators. Furthermore, inspired by the acquired reinforcement learning theory based on Baldwin effect, the proposed algorithm guides individuals to forward or reverse learning and enables the transmission of fitness information between parents and offspring to adapt individuals' acquired fitness. Findings: Global convergence of the proposed algorithm is proved in detail. Numerical simulations are conducted for a set of benchmark functions with different dimensional decision variables. The performance of the proposed algorithm is compared with that of the other evolutionary algorithms published recently. The results indicate that the proposed algorithm can find optimal or closer-to-optimal solutions, and is more competitive than the compared algorithms. Originality/value: The proposed algorithm introduces, integrates and simulates correctly and adequately, for the first time, the mechanisms of sexual reproduction, Baldwin effect and adaptation to GAs by referring to the latest research results of modern biology and evolution theory. © Emerald Group Publishing Limited. Source

Zhao J.,Dalian University of Technology | Liu Q.,Dalian University of Technology | Wang W.,Dalian University of Technology | Pedrycz W.,University of Alberta | Cong L.,Shanghai Baosight Software Co.
IEEE Transactions on Neural Networks and Learning Systems | Year: 2012

An energy system is the one of most important parts of the steel industry, and its reasonable operation exhibits a critical impact on manufacturing cost, energy security, and natural environment. With respect to the operation optimization problem for coke oven gas, a two-phase data-driven based forecasting and optimized adjusting method is proposed, where a Gaussian process-based echo states network is established to predict the gas real-time flow and the gasholder level in the prediction phase. Then, using the predicted gas flow and gasholder level, we develop a certain heuristic to quantify the user's optimal gas adjustment. The proposed operation measure has been verified to be effective by experimenting with the real-world on-line energy data sets coming from Shanghai Baosteel Corporation, Ltd., China. At present, the scheduling software developed with the proposed model and ensuing algorithms have been applied to the production practice of Baosteel. The application effects indicate that the software system can largely improve the real-time prediction accuracy of the gas units and provide with the optimized gas balance direction for the energy optimization. © 2012 IEEE. Source

Wei W.,Shanghai University of Electric Power | Hu S.,Shanghai Baosight Software Co. | Zhao Y.,Shanghai University of Electric Power | Zhao Y.,Shanghai University
Journal of Computational Information Systems | Year: 2011

Motivated by Gallagher's image rescaling detection/estimation method, we propose an improved algorithm that can blindly estimate the scaling ratio of zooming-in or zooming-out image. Calculate the second-order difference along the vertical (horizontal) direction of image. Compute the mean of absolute difference along the horizontal (vertical) direction and obtain a vector. Calculate DFT to the vector and produce the frequency-magnitude curve. Detect the peak frequency in the curve and obtain the scaling ratio along the horizontal (vertical) direction. It is applicable to different interpolation schemes, no matter whether the image has been JPEG compressed before or after interpolation. Experimental results indicate the robustness of the proposed estimator against post-processing. © 2011 by Binary Information Press. Source

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