Towards Generalized Resource Allocation on Evolutionary Multitasking for Multi-Objective Optimization Tingyang Wei South China University of Technology, CHINA Jinghui Zhong South China University of Technology, CHINA Abstract-Evolutionary multitasking optimization (EMTO) is an emerging paradigm for solving several problems simultaneously. Due to the flexible framework, EMTO has been naturally applied to multi-objective optimization to exploit synergy among distinct multi-objective problem domains. However, most studies barely take into account the scenario where some problems cannot converge under restrictive computational budgets with the traditional EMTO framework. To dynamically allocate computational resources for multi-objective EMTO problems, this article proposes a generalized resource allocation (GRA) framework by concerning both theoretical grounds of conventional resource allocation and the characteristics of multi-objective optimization. In the proposed framework, a Digital Object Identifier 10.1109/MCI.2021.3108310 Date of current version: 13 October 2021 Corresponding Author: Jinghui Zhong (jinghuizhong@scut.edu.cn). ©SHUTTERSTOCK.COM/VECTORMINE 20 IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | NOVEMBER 2021 1556-603X/21©2021IEEEhttp://www.SHUTTERSTOCK.COM/VECTORMINE