Variable speed multi-task allocation for mobile crowdsensing based on a multi-objective shuffled frog leaping algorithm

Shen，Xiaoning1; Chen，Qingzhou1; Pan，Hongli1; Song，Liyan2; Guo，Yinan3,4

2022-09-01

10.1016/j.asoc.2022.109330

APPLIED SOFT COMPUTING   Impact Factor & Quartile

1568-4946

1872-9681

In multi-task studies of mobile crowdsensing, the possibility that a user may adopt another travel mode when completing the current task to the next is ignored. In addition, existing methods tend to allocate more tasks to the users with high reputation, which causes that few tasks will be assigned to new users with low reputation. In order to cover these shortages, a constrained multi-objective optimization model of variable speed multi-task allocation is established, which aims to maximize the user rewards and minimize the task completion time simultaneously. Meanwhile, the maximum number of fully paid tasks positively correlated with reputation is set for each user. To solve the constructed model, a three-stage multi-objective shuffled frog leaping algorithm is proposed, which introduces an objective anchored hybrid initialization operator based on heuristic information, a region mining strategy for the archive individuals, a discrete leaping rule to enhance the interaction of individual information and a constraint handling operator to reduce the loss of individual information. The performance of the proposed algorithm is evaluated by comparing it with five state-of-the-art algorithms on both real-world and synthetic instances. Experimental results show that the proposed algorithm can find a set of Pareto optimal allocation solutions with better convergence and distributions.

Multi-objective optimization Multi-task allocation Reward mechanism Three- stage Three-stage shuffled frog leaping algorithm Variable speed

SCI ; EI

English

Others

National Natural Science Foundation of China[61502239];National Natural Science Foundation of China[61973305];National Natural Science Foundation of China[62002148];Natural Science Foundation of Jiangsu Province[BK20150924];

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications

WOS:000861216300011

ELSEVIER

20223112469028

Constrained optimization ; Constraint handling ; Pareto principle

Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory:721.1 ; Optimization Techniques:921.5 ; Systems Science:961

COMPUTER SCIENCE

2-s2.0-85135101350

Scopus

1.B-DAT,CICAEET,School of Automation,Nanjing University of Information Science and Technology,Nanjing,210044,China
2.Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation,Southern University of Science and Technology,Shenzhen,518055,China
3.School of Electromechanical and Information Engineering,China University of Mining and Technology (Beijing),Beijing,100083,China
4.School of Information and Control Engineering,China University of Mining and Technology,Xuzhou,221116,China

Shen，Xiaoning,Chen，Qingzhou,Pan，Hongli,et al. Variable speed multi-task allocation for mobile crowdsensing based on a multi-objective shuffled frog leaping algorithm[J]. APPLIED SOFT COMPUTING,2022,127.

Shen，Xiaoning,Chen，Qingzhou,Pan，Hongli,Song，Liyan,&Guo，Yinan.(2022).Variable speed multi-task allocation for mobile crowdsensing based on a multi-objective shuffled frog leaping algorithm.APPLIED SOFT COMPUTING,127.

Shen，Xiaoning,et al."Variable speed multi-task allocation for mobile crowdsensing based on a multi-objective shuffled frog leaping algorithm".APPLIED SOFT COMPUTING 127(2022).