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Titlebook: Robust Control Theory; Bruce A. Francis,Pramod P. Khargonekar Conference proceedings 1995 Springer-Verlag New York, Inc. 1995 Approximatio

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Tongwen Chen,Li Qiuvice stations. It is impossible to solve this problem optimally in a reasonable time, and consequently we apply a particle swarm optimization (PSO) method to solve this multi-objective continuous-time problem using a goal attainment technique. Finally, to show the effectiveness of the proposed PSO,
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Mustafa H. Khammashvice stations. It is impossible to solve this problem optimally in a reasonable time, and consequently we apply a particle swarm optimization (PSO) method to solve this multi-objective continuous-time problem using a goal attainment technique. Finally, to show the effectiveness of the proposed PSO,
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Li Qiu,Daniel E. Millern the literature and enables the relaxation of the common assumption that only one activity at a time disturbs the starting time of a successor activity, rather limiting the joint probability of disruption of the preceding activities to a given probability level. The results obtained with the propos
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Mario A. Rotea,Pramod P. KhargonekarThis chapter summarizes a body of work developed over the years on PCP-based scheduling to take advantage of such properties. In particular, the chapter presents an overview on a number of original algorithms for efficiently finding a solution to a scheduling problem, for generating robust schedules
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