Topology Optimisation Using MPBILs and Multi-Grid Ground Element
Source abstract
Abstract
This paper aims to study the comparative performance of original multi-objective population-based incremental learning (MPBIL) and three improvements of MPBIL. The first improvement of original MPBIL is an opposite-based concept, whereas the second and third method enhance the performance of MPBIL using the multi and adaptive learning rate, respectively. Four classic multi-objective structural topology optimization problems are used for testing the performance. Furthermore, these topology optimization problems are improved by the method of multiple resolutions of ground elements, which is called a multi-grid approach (MG). Multi-objective design problems with MG design variables are then posed and tackled by the traditional MPBIL and its improved variants. The results show that using MPBIL with opposite-based concept and MG approach can outperform other MPBIL versions.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Topology Optimization in Engineering · Advanced Multi-Objective Optimization Algorithms · Metaheuristic Optimization Algorithms Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Aeronautical Engineering and Commercial Pilot, International Academy of Aviation Industry, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
Sustainable and Infrastructure Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen City 40002, Thailand
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