Robust scheduling is an effective way to solve job-shop scheduling problem (JSP) under a dynamic and stochastic environment with uncertainties, which may lead to numerous schedule disruptions. Maintaining the optimiza...
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Robust scheduling is an effective way to solve job-shop scheduling problem (JSP) under a dynamic and stochastic environment with uncertainties, which may lead to numerous schedule disruptions. Maintaining the optimization obtained, the robust schedule is more stable in execution. The vast majority of the researches on robust scheduling concentrate on the development of the robustness and stabilization with an optimization target that minimizes makespan. However, other optimization targets are needed in reality, and in this paper, we introduce another optimization target that maximizes the payload of the machine, which can reflect the capacity of machine. This work applies a two-step way to achieve a robust schedule. A baseline schedule in the deterministic environment is generated first, which pursues standard optimization criterions, and then the temporal buffers are inserted into the baseline schedule which make the schedule absorb some level of unexpected disruption without rescheduling. According to the payload of each machine which should be close to the maximum at any time in execution, we can get each size of the temporal buffers inserted into the different operations. An extensive experiment is used to show the relative performance of the proposed robust schedule. It is shown that the schedule is robust and stable under the stochastic disturbance coupling with minimal makespan tardiness and symmetry payload.
The problem of access control across multiple security domains in data sharing environment is addressed and a rule-based algorithm for role mapping across multi-domains is presented. The algorithm resolves efficiently...
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The problem of access control across multiple security domains in data sharing environment is addressed and a rule-based algorithm for role mapping across multi-domains is presented. The algorithm resolves efficiently the conflicts of cyclic inheritance and separation of duties, and the problem of regression inheritance. The algorithm takes the “Least privilege theorem” into account and prohibits accesses from illegal domains. Further more, the algorithm makes the establishment of role mapping across multi-domains more efficiently by preserving historical information of role mapping paths established successfully before, and satisfies preferably the access control requirement across dynamic multi-domains in data sharing environment. Evaluation by access instances shows the efficiency of our algorithm.
作者：
Selamat, AliLim, Pei-Geok
Department of Software Engineering Faculty of Computer Science and Information System Malaysia
The rapid growth of computer technologies and the advent of the World Wide Web have increased the amount and the complexity of multimedia information. A content-based image retrieval (CBIR) system has been developed a...
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ISBN:
(纸本)9781424438853
The rapid growth of computer technologies and the advent of the World Wide Web have increased the amount and the complexity of multimedia information. A content-based image retrieval (CBIR) system has been developed as an efficient image retrieval tool, whereby the user can provide their query to the system to allow it to retrieve the user's desired image from the image database. However, the traditional relevance feedback of CBIR has some limitations that will decrease the performance of the CBIR system, such as the imbalance of training-set problem, classification problem, limited information from user problem, and insufficient training-set problem. Therefore, in this study, we proposed an enhanced relevance-feedback method to support the user query based on the representative image selection and weight ranking of the images retrieved. The support vector machine (SVM) has been used to support the learning process to reduce the semantic gap between the user and the CBIR system. From these experiments, the proposed learning method has enabled users to improve their search results based on the performance of CBIR system. In addition, the experiments also proved that by solving the imbalance training set issue, the performance of CBIR could be improved.
Moving horizon estimation for discrete-time nonlinear systems is addressed by using fast optimization algorithms for which stability results under general conditions are ensured. The solution of the on-line moving hor...
Moving horizon estimation for discrete-time nonlinear systems is addressed by using fast optimization algorithms for which stability results under general conditions are ensured. The solution of the on-line moving horizon estimation problem is obtained by using the sampling time to solve a reference problem with model-predicted measurements while waiting for the next measurement. In order to correct the resulting solution, a quick nonlinear programming sensitivity calculation is accomplished as soon as the new measurement becomes available. The stability properties of such moving horizon estimation algorithm is proved under general conditions, which make the overall approach suitable for real settings with strong nonlinearities.
This paper presents a method for estimating the torque and speed of line-start induction motor (IM). IM is being used for various purposes because that is a high trust machine for the load mechanism and can be used ea...
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The support vector domain description (SVDD) is a popular kernel method for outlier detection, which tries to fit a class of data with a sphere and uses a few target objects to support its decision boundary. The probl...
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Satisfiability modulo theories (SMT) play a key role in verification applications. A crucial SMT problem is to combine separate theory solvers for the union of theories. In previous work, the simplex method is used to...
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Satisfiability modulo theories (SMT) play a key role in verification applications. A crucial SMT problem is to combine separate theory solvers for the union of theories. In previous work, the simplex method is used to determine the solvability of constraint systems and the equalities implied by constraint systems are detected by a multitude of applications of the dual simplex method. We present an effective simplex tableau-based method to identify all implicit equalities such that the simplex method is harnessed to an irreducible minimum. Experimental results show that the method is feasible and effective.
Dynamic programming provides a method to solve hybrid optimal control problems. This contribution extends existing numerical methods originally developed for purely continuous systems, to a class of hybrid systems wit...
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ISBN:
(纸本)9783902661593
Dynamic programming provides a method to solve hybrid optimal control problems. This contribution extends existing numerical methods originally developed for purely continuous systems, to a class of hybrid systems with autonomous as well as controlled switching behavior. The hybrid dynamics is approximated by a locally consistent discrete Markov decision process. The original optimal control problem is then reformulated for the Markov decision process and solved by standard dynamic programming methods. The convergence of the discrete approximation to the original problem is ensured. The viability of the numerical scheme is illustrated by a two gear transmission system used previously in literature.
A communication-based distributed model predictive control scheme for a set of dynamically decoupled autonomous systems (agents) is proposed. The individual dynamics are described by discrete-time linear systems. Loca...
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In current manufacturing systems, short times for product development and ramp-up as well as high production rates and customized products are of increasing importance. To push the efficiency (and thus the economic ga...
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