Abstract The optimization of the resource-constrained project scheduling is an NP-hard problem. Complexity of the algorithm for solving this problem increases exponentially with the increase of resource constraints. Therefore, traditional optimization methods based on Excel tables cannot calculate the efficient allocation of resources, which will affect the scheduling of project management resources. The optimization problem like multiple resource-constrained project scheduling demands... The optimization of the resource-constrained project scheduling is an NP-hard problem. Complexity of the algorithm for solving this problem increases exponentially with the increase of resource constraints. Therefore, traditional optimization methods based on Excel tables cannot calculate the efficient allocation of resources, which will affect the scheduling of project management resources. The optimization problem like multiple resource-constrained project scheduling demands an optimization method based on genetic algorithm, which adopts the decimal encoding based on activity priority combined with the storage of the adjacency matrix in order to effectively solve unauthorized phenomenon in activity scheduling. It also adopts preemption mode of allocation of resources in activities to avoid conflict in resource allocation. Besides, we designs C language program that realizes heuristic genetic algorithm, which can find out the most excellent duration that meets the resource constraints through multiple iterations. Finally, the practical results indicate that genetic algorithm can quickly and efficiently solve this problem. Read More Read Less

Abstract A detailed investigation on the production, processing and sales of Sichuan agricultural products was made. Issues like how to bring into full play the regional advantages of Sichuan agricultural products and how to promote the advantageous resource allocation and competitiveness of agricultural products in market economy were also probed. Suggestions and schemes for the e-commerce service system of Sichuan agricultural... A detailed investigation on the production, processing and sales of Sichuan agricultural products was made. Issues like how to bring into full play the regional advantages of Sichuan agricultural products and how to promote the advantageous resource allocation and competitiveness of agricultural products in market economy were also probed. Suggestions and schemes for the e-commerce service system of Sichuan agricultural products were proposed through the analysis framework of fuzzy comprehensive evaluation method and improved D&M model. Read More Read Less

Abstract The credit risk evaluation of corporate bond is one of the difficult and hot research fields in the related research and plays a key role for corporate financing. Based on the fuzzy theory and analytic hierarchy process, a new credit risk evaluation model of corporate bond is presented. First an evaluation indicator system of credit risk of corporate bond is... The credit risk evaluation of corporate bond is one of the difficult and hot research fields in the related research and plays a key role for corporate financing. Based on the fuzzy theory and analytic hierarchy process, a new credit risk evaluation model of corporate bond is presented. First an evaluation indicator system of credit risk of corporate bond is designed through analyzing the characteristics of the evaluation indicator with more details; Second, analytic hierarchy process is used to determine the level of different indicators and multistage comprehensive fuzzy evaluation is used to evaluate the credit risk of corporate bond. Finally, corporate bond of 10 enterprises are taken for examples to evaluate the credit risk and verify the validity and feasibility of the model and the experimental results show that the model can evaluate the credit risk of different corporate bond of different enterprises practically. Read More Read Less

Abstract New application systems generated by composition of web services dynamically have become a development trend in network environment.However, since a variety of external services are invoked with different quality of service during processing,the problem of how to keep the execution stable must be addressed in order to improve the reliability and availability of the combination of services.In this paper, an... New application systems generated by composition of web services dynamically have become a development trend in network environment.However, since a variety of external services are invoked with different quality of service during processing,the problem of how to keep the execution stable must be addressed in order to improve the reliability and availability of the combination of services.In this paper, an approach of exception detection is presented for web service composition by improved Bayesian network. Firstly, the topological structure of Bayesian network is established, where the causal relationships between underlying web services are mapped to Bayesian network in service combination process. The conventional Bayesian network algorithm is improved to satisfy the demand of better conversion from nodes in web service composition to nodes in Bayesian network.Secondly, the parameter setting in Bayesian network is explored for determining the prior probability of service nodes and the conditional probability of service output node. Thirdly, the algorithm of the improved exception detection model is introduced, with the aim of locating the web services that cause exceptions in the execution of composite services.Lastly, a case study is given and the results analysis is also conducted. The results show that the presented approach not only considers the uncertainty during exception detection, but also can identify the exception web services in the process. Read More Read Less

Abstract Using computer vision library OpenCV, a method of automatic recognition high points of scraped workpiece surface is presented. The image is dealt with by background subtraction, Median filtering, morphological processing, image negates, contour finding and drawing contours. In order to accurately and efficiently recognize the high-point contours and mark its center positions, mathematical morphology and specific processing function were used.... Using computer vision library OpenCV, a method of automatic recognition high points of scraped workpiece surface is presented. The image is dealt with by background subtraction, Median filtering, morphological processing, image negates, contour finding and drawing contours. In order to accurately and efficiently recognize the high-point contours and mark its center positions, mathematical morphology and specific processing function were used. Read More Read Less

Abstract Ladle is an important container in metallurgy industry, and its lifetime is very important for the natural production of enterprise. The stand or fall of refractory lining of ladle decides its lifetime, yet thermal stress is the direct reason of causing refractory lining breakage. In this paper the structure of ladle mainly by changing the structure of bottom with finite... Ladle is an important container in metallurgy industry, and its lifetime is very important for the natural production of enterprise. The stand or fall of refractory lining of ladle decides its lifetime, yet thermal stress is the direct reason of causing refractory lining breakage. In this paper the structure of ladle mainly by changing the structure of bottom with finite element method is designed, and three scheme models are put forward. By analyzing and comparing stress field of the three ladle models, finally an optimization scheme is put forward. The experiment results indicate that the lifetime of ladle gains obvious increasement, and the rationality and practicability of the scheme have been proved. The method is feasible to improve ladles lifetime. Read More Read Less

Abstract The importance of information sharing in supply chain management is a matter of consensus between practitioners and researchers. Information sharing can increase supply chain efficiency by reducing inventories and smoothing production. Studies from different and recognised authors are reviewed, compiled and analyzed in three aspects. First, the types of shared information in supply chain are summarized. After, the value of... The importance of information sharing in supply chain management is a matter of consensus between practitioners and researchers. Information sharing can increase supply chain efficiency by reducing inventories and smoothing production. Studies from different and recognised authors are reviewed, compiled and analyzed in three aspects. First, the types of shared information in supply chain are summarized. After, the value of different shared information and the factors which affect its value are presented. Moreover, the methodologies used in literature are detailed. The paper concludes with some future directions for theory construction and empirical research. Read More Read Less

Abstract At present, iron and steel enterprise develops towards the direction with many procedure, many process, many variety and many specification, and reaches hundreds and thousands of product series and product mix, how to plan, organize and control steel production, production schedule of its product line are key issues. According to the main characteristics of production line of iron and steel... At present, iron and steel enterprise develops towards the direction with many procedure, many process, many variety and many specification, and reaches hundreds and thousands of product series and product mix, how to plan, organize and control steel production, production schedule of its product line are key issues. According to the main characteristics of production line of iron and steel enterprise, how to make aggregate production planning of iron and steel enterprise are analyzed. An aggregate production plan model of product line of iron and steel enterprise is proposed, which is calculated by using standard library function of the Matlab7.0 genetic algorithm toolbox to program. Penalty function was adopted in the course of getting solution. These parameters of scale of father population, crossover probability, mutation probability and penalty factor were combined and optimized. The result obtained is in accordance with the actual conditions of this enterprise basically that the optimization solution to production plans of real iron and steel enterprise by using the algorithm. Read More Read Less

Abstract Vehicle Routing Problem (VRP) is a hot issue in the field of logistics. Furthermore, the Vehicle Routing Problem with Time-Windows (VRPTW) is an additional constraint of the customer access time windows based on the VRP. It becomes a noticeable problem with the development of logistics distribution and the just-intime distribution demand from customers, which increases a visiting window to traditional... Vehicle Routing Problem (VRP) is a hot issue in the field of logistics. Furthermore, the Vehicle Routing Problem with Time-Windows (VRPTW) is an additional constraint of the customer access time windows based on the VRP. It becomes a noticeable problem with the development of logistics distribution and the just-intime distribution demand from customers, which increases a visiting window to traditional VRP. This paper firstly analyzes the distribution vehicle scheduling optimization problem with time-windows. Subsequently, through transforming the capacity and soft time-windows constraint into objective constraint, the authors establish a non-full loaded VSP model. Moreover, genetic algorithm is used to solve this problem, where natural number is adopted to realize problem coding and the maximum reservation crossover and improved inverse mutation technology are used to generate new individuals. Finally through the simulation experiment, the results verify its feasibility and effectiveness. Read More Read Less

Abstract High-speed cold roll-beating forming technique is a new near-net plastic forming method that the intermittent high-speed roll-beating is used to achieve dynamic impact local loading, and that is fast, transient, high impact, large deformation of the complex forming process. For this forming process, the main stress method is employed to derive an analytic formula for the deformation force. Taking into... High-speed cold roll-beating forming technique is a new near-net plastic forming method that the intermittent high-speed roll-beating is used to achieve dynamic impact local loading, and that is fast, transient, high impact, large deformation of the complex forming process. For this forming process, the main stress method is employed to derive an analytic formula for the deformation force. Taking into account the main stress method can not reflect impact factors such as high-speed transient roll beating in process of this analytic solution, then the ABAQUS/Explicit is applied to simulate for highspeed cold roll- beating. The regression analysis is used to correct for the analytic formula based on simulation results, which makes the analytic formula more accurate reflection of deformation force of the different technological parameters of high-speed cold roll-beating. The forming experiments are carried out with self developed high-speed cold roll-beating experimental equipment and the experimental of deformation force is measured to verify the correctness of the corrected analytic formula. Read More Read Less

Abstract Aiming at deficiencies of the ability for preserving local nonlinear structure of recently proposed Regularized Orthogonal Linear Discriminant Analysis (ROLDA) for dimensionality reduction, a kind of dimensionality reduction algorithm named Regularized Orthogonal Local Fisher Discriminant Analysis (ROLFDA) is proposed in the paper, which is originated from ROLDA. The algorithm introduce the idea of local structure preserving in Local Fisher Discriminant... Aiming at deficiencies of the ability for preserving local nonlinear structure of recently proposed Regularized Orthogonal Linear Discriminant Analysis (ROLDA) for dimensionality reduction, a kind of dimensionality reduction algorithm named Regularized Orthogonal Local Fisher Discriminant Analysis (ROLFDA) is proposed in the paper, which is originated from ROLDA. The algorithm introduce the idea of local structure preserving in Local Fisher Discriminant Analysis (LFDA) on the basic of ROLDA, following properties of ROLDA and strengthening the ability for capturing local structure information of data with nonlinear structures. Experiments on real face datasets demonstrate the effectiveness of our proposed algorithm. Read More Read Less

Abstract Supply chain demand prediction plays a very important role for enterprises to realize sales and markets management target effectively, especially for fresh agricultural product enterprises. A new model for supply chain demand prediction for fresh agricultural product enterprises is presented based on improved BP neural network. First the advantages and disadvantages of BP neural network algorithm are analyzed when it... Supply chain demand prediction plays a very important role for enterprises to realize sales and markets management target effectively, especially for fresh agricultural product enterprises. A new model for supply chain demand prediction for fresh agricultural product enterprises is presented based on improved BP neural network. First the advantages and disadvantages of BP neural network algorithm are analyzed when it is used in supply chain demand prediction; Second, Legendre wavelets algorithm is used to speed up the convergence and improve the prediction accuracy of original BP neural network algorithm and based on this the paper advances a new supply chain demand prediction model for fresh agricultural product enterprises. Finally, certain fresh agricultural product enterprise is taken for example to verify the validity and feasibility of the model and the experimental results show that the model can improve prediction accuracy and decrease the calculation time and can be used for supply chain demand prediction practically. Read More Read Less

Abstract The hospital customer classification is very important for the integration and allocation of hospital resources, can greatly enhance the market competitiveness of the hospital. Support Vector Machine (SVM) is an approach to solve classification problem by using optimization method. Selecting different kernel parameters can construct different classifiers, meanwhile parameters decide their learning and generalization ability. In order to solve the... The hospital customer classification is very important for the integration and allocation of hospital resources, can greatly enhance the market competitiveness of the hospital. Support Vector Machine (SVM) is an approach to solve classification problem by using optimization method. Selecting different kernel parameters can construct different classifiers, meanwhile parameters decide their learning and generalization ability. In order to solve the limitation of selecting parameters by experience, so the particle swarm (PSO) pattern search algorithm is proposed to search optimal parameters and take them into the practice of hospital customer classification; The PSO mode search algorithm is to combine the advantages of PSO algorithm and pattern search algorithm, PSO mode search algorithm has strong global search capability and good advantage of local convergence. The result of experiment shows that this method is not only efficient, but also to search the optimal parameters achieving a high accuracy, which is an effective method of SVM parameter optimization. Read More Read Less