Browsing by Author "Sun, SH"

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A project scheduling and staff assignment model considering learning effect
(2006-05-01)
Wu, MC
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Sun, SH
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工業工程與管理學系
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Department of Industrial Engineering and Management
In a multi-project environment, we sometimes need to periodically schedule the tasks for each project and assign staff to the tasks. Such a decision-making problem has been studied in literature; however, learning effect of staff has not been considered in previous studies. This research formulates a mixed nonlinear program for project scheduling and staff allocation problems, which considers learning effect of staff. The objective function is to minimize outsourcing costs. A genetic algorithm (GA) is proposed to solve the problem. Experiments for solving various sizes of test problems has been carried out to validate the proposed GA.
Vector quantization based on genetic simulated annealing
(2001-07-01)
Huang, HC
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Pan, JS
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Lu, ZM
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Sun, SH
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Hang, HM
Genetic algorithm (GA) has been successfully applied to codebook design for vector quantization (VQ). However, most conventional GA-based codebook design methods need long runtime because candidate solutions must be fine tuned by LBG. In this paper, a partition-based GA is applied to codebook design, which is referred to as genetic vector quantization (GVQ). In addition, simulated annealing (SA) algorithm is also used in GVQ to get more promising results and the corresponding method is referred to as GSAVQ. Both GVQ and GSAVQ use the linear scaling technique during the calculation of objective functions and use special crossover and mutation operations in order to obtain better codebooks in much shorter CPU time. Experimental results show that both of them save more than 71-87% CPU time compared to LEG. For different codebook sizes, GVQ outperforms LEG by 1.1-2.1 dB in PSNR, and GSAVQ outperforms LBG by 1.2-2.2 dB in PSNR. In addition, GVQ and GSAVQ need a little longer CPU time than, the maximum decent (MD) algorithm, but they outperform MD by 0.2-0.5 dB in PSNR. (C) 2001 Elsevier Science B.V. All rights reserved.