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SCHEDULING JOBS WITH GENERAL LEARNING FUNCTIONS 被引量:3
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作者 Li-Yan WANG Jian-Jun WANG +1 位作者 Ji-Bo WANG en-min feng 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2011年第1期119-125,共7页
This paper deals with single-machine scheduling problems with a more general learning effect based on sum-of-processing-time. In this study, sum-of-processing-time-based learning effect means that the processing time ... This paper deals with single-machine scheduling problems with a more general learning effect based on sum-of-processing-time. In this study, sum-of-processing-time-based learning effect means that the processing time of a job is defined by a decreasing function of the total normal processing time of jobs that come before it in the sequence. Results show that even with the introduction of the sum-of-processing-time-based learning effect to job processing times, single-machine makespan minimization problems remain polynomially solvable. The curves of the optimal schedule of a total completion time minimization problem are V-shaped with respect to iob normal orocessinz times. 展开更多
关键词 SCHEDULING single machine learning effect MAKESPAN total completion time
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Optimal Control Problem Governed by Semilinear Parabolic Equation and its Algorithm
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作者 Chun-fa Li Xue Yang en-min feng 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2008年第1期29-40,共12页
In this paper, an optimal control problem governed by semilinear parabolic equation which involves the control variable acting on forcing term and coefficients appearing in the higher order derivative terms is formula... In this paper, an optimal control problem governed by semilinear parabolic equation which involves the control variable acting on forcing term and coefficients appearing in the higher order derivative terms is formulated and analyzed. The strong variation method, due originally to Mayne et al to solve the optimal control problem of a lumped parameter system, is extended to solve an optimal control problem governed by semilinear parabolic equation, a necessary condition is obtained, the strong variation algorithm for this optimal control problem is presented, and the corresponding convergence result of the algorithm is verified. 展开更多
关键词 Distributed parameter system strong variation method optimal control adjoint system semilinear parabolic equations
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