As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Taking the irrationality of staff scheduling in China Geography Census (CGC) into consideration, this paper establishes a personnel optimization scheduling model. It is based on some assumptions according to characteristics in CGC's (or National Geographic Conditions Monitoring) production process. As optimal dispatch of personnel involves in large-scale, high dimension and nonlinear problems, the standard genetic algorithm (SGA) has drawbacks of premature and slow convergence, as well as poor local optimization ability. So this paper adopts cloud adaptive parallel simulated annealing genetic algorithm (PCASAGA), which integrates adaptiveness, cloud reasoning with simulated annealing mechanism to improve SGA's performance. And also parallel computing function is introduced. To Take Shandong Remote Sensing Technology Application Center as an example, it shows that PCASAGA is superior to SGA in convergence speed and optimization ability. It also proofs that homogeneous and heterogeneous situations have not only distinction but also connection as influence factors increase, such as number of return to modify (n), quality sampling rate (s) and error rate (e). The distinction is changes of structure's proportion, the former case shows flat or falling trends, and the latter one has no unified state. On another side, the connection is the increased optimal completion time. The findings have guiding significance for staff optimization in National Geographic Conditions Monitoring in aspects of engineering plan, cost calculation and so on.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.