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Blind signal extraction is particularly attractive to solve signal mixture problems while only one or a few source signals are desired. Many desired biomedical signals exhibit distinct periods. A sequential method based on second order statistics is introduced in this paper. One can choose to recover one source signal or all signals in a specific order. The validity and performance of the proposed...
In this paper we focus on the Job Shop Scheduling Problem (JSSP) using Priority Dispatching Rules. Simulation model for makespan optimization is proposed using different Dispatching Rules (DR) for each machine in the shop floor. Collected results are used for learning base construction. This database will be used to develop an inference model able to select the best DR for every new scheduling problem...
The following topics are dealt with: language technologies-an infrastructure for information society; networking, grids, middleware and distributed platforms; business intelligence, information systems and databases; knowledge management and collaboration systems; human computer interaction; technology enhanced learning; information technology in business and government; data mining, statistics and...
Generally, the environment and enterprises' condition are not stable, in order to promote the enterprises' competitive power, managers must continuously improve the business processes' performance. Based on the simulation method and multi-objective optimization theory, the thesis builds a dynamic multi-objective optimization model for business process optimization. Firstly the framework of optimization...
The particle swarm optimization (PSO) algorithm is vulnerable to reach local optimal value. So, this paper presents an adaptive hybrid particles swarm optimization. During the solving process, both crossover operator in genetic algorithm and hyper-mutation are introduced. Referring to the selection mechanism of immune algorithm based on information entropy, the adaptive selections mechanism is proposed...
The performance optimization of many man-made systems belong to simulation-based constrained optimization (SBCO), where the evaluation of both the performance and the constraint have no closed form expression and are based on simulation. The simulation-based estimate of both the performance and the feasibility are usually time-consuming and noisy. So it is of great practical interest to study how...
Design of experiments is often used to better understand or improve the output measures of a simulation model. Traditional cuboidal and spherical designs have been effective when the factor input regions are known. However, often in practice, simulation models have additional stochastic constraints causing the input factor space to be restricted and irregularly shaped. This paper looks into several...
The fuzzy rule sets, which have been widely used in avionic fault diagnosis system, have considerable redundancy that leads to time-consuming faults location process. In this paper, to reduce the redundant rules, a multiple objective genetic algorithm, MOGAII, is used to optimize a fuzzy rule set. The optimization problem with two objectives, the maximization diagnostic capability of the system and...
Urban network traffic is a complex, nonlinear, unstable system and is significantly affected by immeasurable factors. This paper presents an optimal model to the application of signal coordination for urban network based on real-time traffic volumes. It divides a large signalized network into several subgroups. The number of subgroups, phase-time and offsets can be optimized to achieve an optimal...
Aiming at the disadvantages of particle swarm optimization algorithm (PSO), which is easy to trap into local optima and converge slowly in later period of iteration, an improved particle swarm optimization algorithm based on social psychology (BSPSO) was proposed. Unlike the standard PSO algorithm, this BSPSO algorithm used asynchronous version of PSO algorithm, and adopted two strategies (divided...
In this paper, to introduce consistency and diversity, the concept of inertia weight is introduced to a modified genetic particle swarm optimization which was derived from the genetic particle swarm optimization (GPSO) and the differential evolution (DE). The proposed differential genetic particle swarm optimization (DGPSO) is implemented to thirteen well-known constrained optimization functions....
Preview Control is a field well suited for application to systems that have reference signals known a priori. The use of advance knowledge of reference signal can improve the tracking quality of the concerned control system. The classical solution to the Preview Control problem is obtained using the Algebraic Riccati Equation. The solution obtained is good but it is not optimal and has a scope of...
A hybrid differential evolution (HDE) approach derived from both the differential evolution (DE) and the particle swarm optimization (PSO) is proposed. In HDE, individuals in a new generation are created, not only by crossover and mutation operation as in DE, but also by PSO operations. The concepts of inertia weight and neighbor topology are adopted in HDE. The former is employed to provide consistency...
The 0-1 knapsack problem (KP) is a classical NP-hard problem with binary decision variables. The traditional differential evolution (DE) is an effective stochastic parallel search evolutionary algorithm and customized to continuous function optimization. To solve KPs, based on DE, a discrete binary version of differential evolution (DBDE) was employed, where each component of a mutated vector component...
Ensuring system dependability is a key problem to increase the user service performance. Depending on transcendental self-tuning knowledge, a system dependability self-tuning method based on grade optimization is proposed in this paper. It attempts to implement the sustained growth of system dependability by online dependability evaluation, dependability dynamic prediction and self-tuning scheme selection...
This paper presents a modified PSO algorithm for solving constrained multi-objective optimization problems. Based on the constraint dominance concept, the proposed approach defines two sets of selection rules for determining the cognitive and social components of the PSO algorithm. The simulation results to the four constrained multi-objective optimization problems demonstrate the proposed approach...
Passenger transport terminals (PTT) is the cross point of the various transport modes and the place for the travelers to gather, disperse and transfer, so it is the key part of the city's passenger transport system. Witness2007 as a simulation software is constructed to model bus station in Tianjin Railway Station in this paper. Based on above analysis, the paper gave optimized scheme from the view...
In order to enhance the hull erection efficiency and realize the supervisory control dynamically to construction course, this paper applies Fuzzy-timed place Petri net to simulate the process of hull erection. Triangular Fuzzy Number is utilized to denote the uncertain duration, and an advanced Minkowski subtraction is presented in the model. We eliminate the Hatch Coaming Sections, combine the Compartment...
This paper aimed at the cylinder head processing production line of a small equipment manufacturing enterprise, established the discrete digital simulation model of production and analyze the existing bottlenecks in the production line through the simulation run. This study raises the corresponding optimal adjusting program in accordance with the need of workshop production, carries out the comparative...
To meet product diversification and individuation, the paper reconstructed the original single object production line using Flexsim simulation software. Reconstructed model was optimized using the ECRS (eliminate, combine, rearrange, simple) analytic method. The study indicate that the mixed-model production line making up three production line can raise the comprehensive utilization ratio of equipment.
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