Synthesis Constraints Optimized Genetic Algorithm for Autonomous Task Planning and Allocating in MAS

2009 ◽  
Author(s):  
Kailong Zhang ◽  
Xingshe Zhou ◽  
Chongqing Zhao ◽  
Yuan Yao
Keyword(s):  
Genetic Algorithm ◽  
Task Planning

Design and simulation in SAR satellites’ task planning system using genetic algorithm with entropy operator

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wan Liu ◽  
Zeyu Li ◽  
Li Chen ◽  
Dexin Zhang ◽  
Xiaowei Shao
Keyword(s):  
Genetic Algorithm ◽  
Satellite Observation ◽  
Operating Costs ◽  
Planning System ◽  
Task Planning ◽  
Content Type ◽  
Emergency Rescue ◽  
Planning Algorithm ◽  
Planning Problems ◽  
Fitness Calculation

Purpose This paper aims to innovatively propose to improve the efficiency of satellite observation and avoid the waste of satellite resources, a genetic algorithm with entropy operator (GAE) of synthetic aperture radar (SAR) satellites’ task planning algorithm. Design/methodology/approach The GAE abbreviated as GAE introduces the entropy value of each orbit task into the fitness calculation of the genetic algorithm, which makes the orbit with higher entropy value more likely to be selected and participate in the remaining process of the genetic algorithm. Findings The simulation result shows that in a condition of the same calculate ability, 85% of the orbital revisit time is unchanged or decreased and 30% is significantly reduced by using the GAE compared with traditional task planning genetic algorithm, which indicates that the GAE can improve the efficiency of satellites’ task planning. Originality/value The GAE is an optimization of the traditional genetic algorithm. It combines entropy in thermodynamics with task planning problems. The algorithm considers the whole lifecycle of task planning and gets the desired results. It can greatly improve the efficiency of task planning in observation satellites and shorten the entire task execution time. Then, using the GAE to complete SAR satellites’ task planning is of great significance in reducing satellite operating costs and emergency rescue, which brings certain economic and social benefits.

Product cooperative disassembly sequence and task planning based on genetic algorithm

2019 ◽  
Vol 105 (5-6) ◽  
pp. 2103-2120 ◽  
Author(s):  
Yongting Tian ◽  
Xiufen Zhang ◽  
Zehua Liu ◽  
Xingyue Jiang ◽  
Junfang Xue
Keyword(s):  
Genetic Algorithm ◽  
Task Planning ◽  
Disassembly Sequence ◽  
And Task

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
Sign in / Sign up

Export Citation Format

Share Document