Steady State Genetic Algorithm for Ground Station Scheduling Problem

2013 ◽  
Author(s):  
F. Xhafa ◽  
A. Barolli ◽  
M. Takizawa
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Scheduling Problem ◽  
Ground Station

scholarly journals A Heuristic Genetic Algorithm for Regional Targets’ Small Satellite Image Downlink Scheduling Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yan-Jie Song ◽  
Zhong-Shan Zhang ◽  
Kai Sun ◽  
Feng Yao ◽  
Ying-Wu Chen
Keyword(s):  
Genetic Algorithm ◽  
Satellite Image ◽  
Schedule Algorithm ◽  
Scheduling Problem ◽  
Small Satellite ◽  
Task Sequence ◽  
Satellite Mission ◽  
Downlink Scheduling ◽  
Ground Station ◽  
Scale Test

Small satellite image downlink scheduling problem (SSIDSP) is an important part of satellite mission planning. SSIDSP mainly needs to balance how to better match the limited receiving capacity of the ground station with the limited satellite resources. In this paper, regional targets are considered with SSIDSP. We propose a mathematical model that maximizes profit by considering time value and regional targets. A downlink schedule algorithm (DSA) is proposed to complete the task sequence arrangement and generate scheduling results. A heuristic genetic algorithm (HGA) is used to optimize the generated task sequence to achieve higher profit. Three scale test instances are used to test the effectiveness of HGA and DSA. We compare the effect of HGA, basic genetic algorithm (GA), and construction heuristic algorithm. The experimental results proved that the proposed approach ensures the successful completion of observation tasks and is effective for SSIDSP.

A HYBRID PERMUTATION-CODED EVOLUTIONARY ALGORITHM FOR THE EARLY/TARDY SCHEDULING PROBLEM

2010 ◽  
Vol 27 (06) ◽  
pp. 713-725 ◽  
Author(s):  
ALOK SINGH
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Evolutionary Algorithm ◽  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Idle Time ◽  
Scheduling Problem ◽  
Computational Results ◽  
Earliness And Tardiness

In this paper, we have proposed a hybrid permutation-coded steady-state genetic algorithm for a single machine scheduling problem with earliness and tardiness costs and no machine idle time. The steady-state genetic algorithm generates schedules, which are further improved by successive applications of an adjacent pairwise interchange procedure. We have compared our approach against the best approaches reported in the literature. Computational results show the effectiveness of our approach, since it obtained better quality solutions in shorter time.

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