ArticleBiomimetics (Basel, Switzerland)2024
MOBCA: Multi-Objective Besiege and Conquer Algorithm.
Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- FBCA: Flexible Besiege and Conquer Algorithm for Multi-Layer Perceptron Optimization Problems.Biomimetics (Basel, Switzerland) · 2025Article
- An improved multi-objective particle swarm optimization algorithm for the design of foundation pit of rail transit upper cover project.Scientific reports · 2025Article
- Multitask Level-Based Learning Swarm Optimizer.Biomimetics (Basel, Switzerland) · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
The besiege and conquer algorithm has shown excellent performance in single-objective optimization problems. However, there is no literature on the research of the BCA algorithm on multi-objective optimization problems. Therefore, this paper proposes a new multi-objective besiege and conquer algorithm to solve multi-objective optimization problems. The grid mechanism, archiving mechanism, and leader selection mechanism are integrated into the BCA to estimate the Pareto optimal solution and approach the Pareto optimal frontier. The proposed algorithm is tested with MOPSO, MOEA/D, and NSGAIII on the benchmark function IMOP and ZDT. The experiment results show that the proposed algorithm can obtain competitive results in terms of the accuracy of the Pareto optimal solution.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.