Journal
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
Volume 26, Issue 2, Pages 278-289Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEVC.2022.3141819
Keywords
Task analysis; Optimization; Multitasking; Resource management; Statistics; Sociology; Evolutionary computation; Competitive multitasking optimization problem (CMTOP); information transfer; online resources allocation; task selection
Funding
- National Natural Science Foundation of China [61876163, 62106096]
- Hong Kong RGC under GRF [9043148]
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This article introduces a special multitasking optimization problem, called the competitive MTOP (CMTOP), where all tasks' objectives are comparable and the optimal solution is the best among all individual problems. An evolutionary algorithm with online resource allocation strategy and adaptive information transfer mechanism is proposed to solve the CMTOP. Experimental results on benchmark and real-world problems demonstrate the effectiveness and efficiency of the proposed algorithm.
This article introduces a special multitasking optimization problem (MTOP) called the competitive MTOP (CMTOP). Its distinctive characteristics are that all tasks' objectives are comparable, and its optimal solution is the best one among the optimal solutions of all the individual problems. This article proposes an evolutionary algorithm with an online resource allocation strategy and an adaptive information transfer mechanism to solve the CMTOP. The experimental results on benchmark and real-world problems show that our proposed algorithm is effective and efficient.
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