Decomposition-Based Multi-Objective Evolutionary Algorithm with Model-Based Ideal Point Estimation

Wu，Yin; Zheng，Ruihao; Wang，Zhenkun

10.1145/3583131.3590521

2023-07-15

Genetic and Evolutionary Computation Conference (GECCO)

GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference

768-776

JUL 15-19, 2023

null,Lisbon,PORTUGAL

1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES

ASSOC COMPUTING MACHINERY

The ideal point is critical in the multi-objective optimization problem (MOP), which consists of the best value of each objective. It is widely used for normalizing the objective space and guiding the evolution of the population. Since the ideal point cannot know prior, the multi-objective evolutionary algorithm based on decomposition (MOEA/D) takes the best objective values of the population as the estimated ideal point. However, the population-based ideal point estimation may cause the estimated ideal point to be appropriate for (1) no objective or (2) only some objectives. In our analysis, the unreliable estimation deteriorates the performance of MOEA/D. These two scenarios often occur when the MOP with mixed bias (i.e., position-related bias and distance-related bias). To overcome this, we propose to incorporate the model-based ideal point estimation in MOEA/D. The new algorithm (called MOEA/D-MIPE) employs the radial basis function model and a remedy scheme to estimate the ideal point. In experimental studies, we compare MOEA/D-MIPE with seven state-of-The-Art algorithms on various MOPs. The results show that MOEA/D-MIPE has excellent potential.

evolutionary multi-objective optimization ideal point estimation mixed bias multi-objective evolutionary algorithm based on decomposition (MOEA/D)

First ; Corresponding

English

CPCI-S

National Natural Science Foundation of China["62106096","62206120"] ; Characteristic Innovation Project of Colleges and Universities in Guangdong Province, China[2022KTSCX110] ; Shenzhen Technology Plan, China[JCYJ202205301130130311]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Information Systems

WOS:001031455100086

2-s2.0-85167680506

Scopus

School of System Design and Intelligent Manufacturing,Southern University of Science and Technology,Guangdong,Shenzhen,China

Wu，Yin,Zheng，Ruihao,Wang，Zhenkun. Decomposition-Based Multi-Objective Evolutionary Algorithm with Model-Based Ideal Point Estimation[C]. 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES:ASSOC COMPUTING MACHINERY,2023:768-776.