An improved multiobjective optimization evolutionary algorithm based on decomposition with hybrid penalty scheme
| dc.cclicence | N/A | en |
| dc.contributor.author | Guo, Jinglei | |
| dc.contributor.author | Shao, Miaomiao | |
| dc.contributor.author | Jiang, Shouyong | |
| dc.contributor.author | Yang, Shengxiang | |
| dc.date.acceptance | 2020-03 | |
| dc.date.accessioned | 2020-05-19T12:55:20Z | |
| dc.date.available | 2020-05-19T12:55:20Z | |
| dc.date.issued | 2020-07-08 | |
| dc.description.abstract | The multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem(MOP) into a number of single-objective subproblems. Penalty boundary intersection (PBI) in MOEA/D is one of the most popular decomposition approaches and has attracted significant attention. In this paper, we investigate two recent improvements on PBI, i.e. adaptive penalty scheme (APS) and subproblem-based penalty scheme (SPS), and demonstrate their strengths and weaknesses. Based on the observations, we further propose a hybrid penalty scheme (HPS), which adjusts the PBI penalty factor for each subproblem in two phases, to ensure the diversity of boundary solutions and good distribution of intermediate solutions. HPS specifies a distinct penalty value for each subproblem according to its weight vector. All the penalty values of subproblems increase with the same gradient during the first phase, and they are kept unchanged during the second phase. | en |
| dc.funder | Other external funder (please detail below) | en |
| dc.funder.other | National Natural Science Foundation of China | en |
| dc.identifier.citation | Guo, J., Shao, M., Jiang, S. and Yang, S. (2020) An improved multiobjective optimization evolutionary algorithm based on decomposition with hybrid penalty scheme. Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, Electronic conference, July 2020. | en |
| dc.identifier.uri | https://dora.dmu.ac.uk/handle/2086/19612 | |
| dc.language.iso | en_US | en |
| dc.peerreviewed | Yes | en |
| dc.projectid | 61673331 | en |
| dc.publisher | ACM | en |
| dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
| dc.subject | Decomposition | en |
| dc.subject | Multiobjective evolutionary algorithm | en |
| dc.subject | Penalty boundary intersection | en |
| dc.subject | Adaptive penalty scheme | en |
| dc.subject | Subproblem-based penalty scheme | en |
| dc.subject | Hybrid penalty scheme | en |
| dc.title | An improved multiobjective optimization evolutionary algorithm based on decomposition with hybrid penalty scheme | en |
| dc.type | Conference | en |