ParetoTracker: Understanding Population Dynamics in Multi-objective Evolutionary Algorithms through Visual Analytics

Zherui Zhang; Fan Yang; Ran Cheng; Yuxin Ma

2024

10.1109/TVCG.2024.3456142

IEEE Transactions on Visualization and Computer Graphics   影响因子和分区

2160-9306

Multi-objective evolutionary algorithms (MOEAs) have emerged as powerful tools for solving complex optimization problems characterized by multiple, often conflicting, objectives. While advancements have been made in computational efficiency as well as diversity and convergence of solutions, a critical challenge persists: the internal evolutionary mechanisms are opaque to human users. Drawing upon the successes of explainable AI in explaining complex algorithms and models, we argue that the need to understand the underlying evolutionary operators and population dynamics within MOEAs aligns well with a visual analytics paradigm. This paper introduces ParetoTracker, a visual analytics framework designed to support the comprehension and inspection of population dynamics in the evolutionary processes of MOEAs. Informed by preliminary literature review and expert interviews, the framework establishes a multi-level analysis scheme, which caters to user engagement and exploration ranging from examining overall trends in performance metrics to conducting fine-grained inspections of evolutionary operations. In contrast to conventional practices that require manual plotting of solutions for each generation, ParetoTracker facilitates the examination of temporal trends and dynamics across consecutive generations in an integrated visual interface. The effectiveness of the framework is demonstrated through case studies and expert interviews focused on widely adopted benchmark optimization problems

第一

Department of Computer Science and Engineering, Southern University of Science and Technology, China

Zherui Zhang,Fan Yang,Ran Cheng,et al. ParetoTracker: Understanding Population Dynamics in Multi-objective Evolutionary Algorithms through Visual Analytics[J]. IEEE Transactions on Visualization and Computer Graphics,2024,PP(99).

Zherui Zhang,Fan Yang,Ran Cheng,&Yuxin Ma.(2024).ParetoTracker: Understanding Population Dynamics in Multi-objective Evolutionary Algorithms through Visual Analytics.IEEE Transactions on Visualization and Computer Graphics,PP(99).

Zherui Zhang,et al."ParetoTracker: Understanding Population Dynamics in Multi-objective Evolutionary Algorithms through Visual Analytics".IEEE Transactions on Visualization and Computer Graphics PP.99(2024).