Shanghai Baosight Software Co.

Shanghai, China

Shanghai Baosight Software Co.

Shanghai, China
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Liu L.-L.,Shanghai University | Zhao G.-P.,Shanghai University | Ou'Yang S.-S.,Shanghai Baosight Software Co | Yang Y.-J.,Shanghai Baosight Software Co
International Journal of Advanced Manufacturing Technology | Year: 2011

Order planning and scheduling has become a significant challenge in machine tool enterprises, who want to meet various demands of different customers and make full use of existing resources in enterprises simultaneously. Based on the Theory of Constraints, a three-stage order planning and scheduling solution is proposed to optimize the whole system performance with bottleneck resources' capability as the constraints. After the identification of bottleneck resources, multicriteria priority sequencing is made with order per-contribution rate, order delivery urgency, and customer importance as the evaluation criteria, and the evaluation result deduced from the ideal point function can decide the production mode of all orders and products. Then, a PSO-based multiobjective optimization model is set up with minimizing bottleneck machines' makespan and minimizing total products' tardiness as the two objectives. Finally, the proposed solution is applied in one machine tool enterprise by integrating into Baosight MES (Manufacturing Execution System) system. In addition, some comparisons are carried out to evaluate the proposed PSO optimization method. The comparison with actual report shows that PSO can satisfy enterprise's needs better than before; the comparisons with genetic algorithm and ant colony optimization algorithms indicate that PSO is more effective than the others because of its faster convergence rate. © 2011 Springer-Verlag London Limited.


Tao L.,Tongji University | Hao Y.,Tongji University | Yijie H.,Rabun Gap Nacoochee School | Chunfeng S.,Shanghai Baosight Software Co.
Mathematical Problems in Engineering | Year: 2017

Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1) the predictive power of a pattern varies a great deal for different shapes and (2) each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance. © 2017 Lv Tao et al.


Zhang J.,Shanghai JiaoTong University | Zhang J.,Huazhong University of Science and Technology | Zhang P.,Shanghai JiaoTong University | Yang J.,Shanghai Baosight Software Co. | Huang Y.,Shanghai Baosight Software Co.
Advanced Materials Research | Year: 2012

This paper deals with the Job Shop Scheduling Problem with the minimization of makespan as the objective. A novel meta-heuristic named imperialist competitive algorithm (ICA) is adopted to solve the problem. Since appropriate design of the parameters has a significant impact on the performance of the algorithm, the parameters were chosen based on orthogonal test. A local search strategy based on critical path and critical block was used to improve the performance of the algorithm. At last the algorithm was tested on a set of standard benchmark instances, and the computational results showed that the algorithm proposed performed well in both convergence rate and better global optima achievement. © (2012) Trans Tech Publications.


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 Company
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.


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.


Yu W.,Shanghai University of Engineering Science | Kai W.,Shanghai Baosight Software Co. | Chen Y.,Shanghai University of Engineering Science
2016 IEEE 8th International Power Electronics and Motion Control Conference, IPEMC-ECCE Asia 2016 | Year: 2016

The Phasor Measurement Unit(PMU) is used for accurate measurement of synchronous phasor of voltages and currents at separated points across the power grid and are widely installed at the transmission level. As the next point of setup in smart grid, PMU is necessary for components control, fault detection and control, energy management in distribution network. This paper first illustrates the architecture of PMU setup that has been fully designed by the authors and then describes the challenge of designing and implementing which integrates field measurements to deliver Global Positioning System (GPS) synchronized phasor data to the distribution networks. By using this platform, our efforts have provided the real-time data detected, power quality analysis and direction to future efforts to analyze data in cloud calculation, harmonic state estimation, etc. © 2016 IEEE.


Tan Y.-Y.,Northeastern University China | Song J.-H.,Shanghai Baosight Software Ltd Company | 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.


Liu S.-X.,Northeastern University China | Song J.-H.,Shanghai Baosight Software Ltd Company
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.


Tan Y.-Y.,Northeastern University China | Song J.-H.,Shanghai Baosight Software Ltd Company | Liu S.-X.,Northeastern University China
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | Year: 2012

Steelmaking-refining-continuous casting is one of the key manufacturing processes in steel production, for which the optimal scheduling is an effective way for reducing the energy consumption and improving the production efficiency. By considering the required processing time and the technical constrains, we proposed a hybrid two-phase algorithm for the steel production, based on the scatter search (SS) method and the mathematical programming. In the first phase, the SS algorithm determines the order of the steelmaking-refining process and the technical sequence for each of them, based on the normal processing time. In the second phase, the solution obtained in the first phase is transformed into a temporal constraint network graph, and a mixed integer programming model with controllable processing time is built. The machine waiting time, the heat waiting time and the maximum completion time are minimized by using CPLEX. Totally, 14 different sets of randomly data collected from a Chinese iron and steel plant are used to test the model and the hybrid algorithm, and the results are compared with the practical results of the plant. The impact of the different weights for the waiting time on the effectiveness and efficiency of the hybrid algorithm is analyzed and compared with that of the combined genetic local search (GLS) algorithm and mathematical programming. Computational results show that the mathematical model and the two-stage algorithm are effective for solving the steelmaking-refining-continuous casting scheduling problem.


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Shanghai Baosight Software Co. | Date: 2011-07-19

Magnetic encoders; computers; computer operating software; computer peripheral devices; microprocessors, being computer hardware; computer central processing units; computer operating programs, recorded. Computer programming; rental of computer software; updating and design of computer software; maintenance of computer software; recovery of computer data; computer systems analysis; rental of computers.

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