Decomposition with adaptive composite norm for evolutionary multi-objective combinatorial optimization

Zheng，Ruihao1; Wu，Yin3; Li，Genghui1; Zhang，Yu1; Wang，Zhenkun1,2

2024-04-01

10.1016/j.swevo.2024.101503

Swarm and Evolutionary Computation   影响因子和分区

2210-6502

The multi-objective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multi-objective problem into a series of single-objective subproblems for collaborative optimization. The weighted sum (WS) method and the Tchebycheff (TCH) method are the two most popular scalarization methods. They have pros and cons in solving multi-objective combinatorial optimization problems (MOCOPs) the WS method allows MOEA/D to converge faster than the TCH method; the WS-based MOEA/D cannot obtain unsupported non-dominated vectors, while the TCH-based one can overcome this shortcoming. This inspired us to use the WS method to drive the population towards the Pareto front and then switch to the TCH method to maintain a more diverse population. To better balance convergence and diversity, we propose a new scalarization strategy called adaptive composite norm (ACN). The ACN strategy can combine the WS and the TCH with dynamic weighting. The experiments consider 16 instances including 4 MOCOPs and run on the PlatEMO. Results reveal that MOEA/D-ACN can rank first and significantly outperform the other evolutionary multi-objective combinatorial optimization algorithms on almost all instances.

Combinatorial optimization Decomposition Evolutionary algorithm Evolutionary multi-objective optimization Multi-objective optimization

SCI ; EI

英语

第一 ; 通讯

2-s2.0-85185886763

Scopus

1.School of System Design and Intelligent Manufacturing,Southern University of Science and Technology,Shenzhen,Guangdong,China
2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,Guangdong,China
3.Thrust of Artificial Intelligence,The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,Guangdong,China

Zheng，Ruihao,Wu，Yin,Li，Genghui,et al. Decomposition with adaptive composite norm for evolutionary multi-objective combinatorial optimization[J]. Swarm and Evolutionary Computation,2024,86.

Zheng，Ruihao,Wu，Yin,Li，Genghui,Zhang，Yu,&Wang，Zhenkun.(2024).Decomposition with adaptive composite norm for evolutionary multi-objective combinatorial optimization.Swarm and Evolutionary Computation,86.

Zheng，Ruihao,et al."Decomposition with adaptive composite norm for evolutionary multi-objective combinatorial optimization".Swarm and Evolutionary Computation 86(2024).