A Novel Distributed Method For Time-Critical Task Allocation Problems In Multi-UAV System

2021 ◽  
Author(s):  
Jianmin Liu ◽  
Qi Wang ◽  
Yongjun Xu ◽  
Cunzhuang Liu
Keyword(s):  
Task Allocation ◽  
Allocation Problems ◽  
Critical Task ◽  
Time Critical ◽  
Multi Uav ◽  
Distributed Method

Bee-inspired task allocation algorithm for multi-UAV search and rescue missions

2020 ◽  
Vol 16 (4) ◽  
pp. 252
Author(s):  
Heba Kurdi ◽  
Shiroq Al Megren ◽  
Ebtesam Aloboud ◽  
Abeer Ali Alnuaim ◽  
Hessah Alomair ◽  
...  
Keyword(s):  
Task Allocation ◽  
Search And Rescue ◽  
Allocation Algorithm ◽  
Multi Uav

scholarly journals Iterated Local Search for Time-extended Multi-robot Task Allocation with Spatio-temporal and Capacity Constraints

2019 ◽  
Vol 28 (2) ◽  
pp. 347-360 ◽  
Author(s):  
Hakim Mitiche ◽  
Dalila Boughaci ◽  
Maria Gini
Keyword(s):  
Local Search ◽  
Task Allocation ◽  
Iterated Local Search ◽  
Spatial Constraints ◽  
Parameters Tuning ◽  
Temporal And Spatial ◽  
Spatio Temporal ◽  
Robot Task ◽  
Time Critical ◽  
Multi Robot

Abstract We propose a method for task allocation to multiple physical agents that works when tasks have temporal and spatial constraints and agents have different capacities. Assuming that the problem is over-constrained, we need to find allocations that maximize the number of tasks that can be done without violating any of the constraints. The contribution of this work is the study of a new multi-robot task allocation problem and the design and the experimental evaluation of our approach, an iterated local search that is suitable for time critical applications. We created test instances on which we experimentally show that our approach outperforms a state-of-the-art approach to a related problem. Our approach improves the baseline’s score on average by 2.35% and up to 10.53%, while responding in times shorter than the baseline’s, on average, 1.6 s and up to 5.5 s shorter. Furthermore, our approach is robust to run replication and is not very sensitive to parameters tuning.

Decentralized task allocation for heterogeneous multi-UAV system with task coupling constraints

2020 ◽  
Vol 77 (1) ◽  
pp. 111-132 ◽  
Author(s):  
Fang Ye ◽  
Jie Chen ◽  
Qian Sun ◽  
Yuan Tian ◽  
Tao Jiang
Keyword(s):  
Task Allocation ◽  
Coupling Constraints ◽  
Multi Uav

POPULATION SIZE MODELING FOR GA IN TIME-CRITICAL TASK SCHEDULING

2011 ◽  
Vol 22 (03) ◽  
pp. 603-620 ◽  
Author(s):  
WEI SUN
Keyword(s):  
Genetic Algorithms ◽  
Population Size ◽  
Task Scheduling ◽  
Scheduling Problems ◽  
Success Ratio ◽  
Critical Task ◽  
Time Critical

Genetic algorithms (GAs) have been well applied in solving scheduling problems and their performance advantages have also been recognized. However, practitioners are often troubled by parameters setting when they are tuning GAs. Population Size (PS) has been shown to greatly affect the efficiency of GAs. Although some population sizing models exist in the literature, reasonable population sizing for task scheduling is rarely observed. In this paper, based on the PS deciding model proposed by Harik, we present a model to represent the relation between the success ratio and the PS for the GA applied in time-critical task scheduling, in which the efficiency of GAs is more necessitated than in solving other kinds of problems. Our model only needs some parameters easy to know through proper simplifications and approximations. Hence, our model is applicable. Finally, our model is verified through experiments.

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