What question did this study set out to answer?

To develop an efficient competitive swarm optimizer-based search algorithm with a novel particle updating strategy to solve large-scale multiobjective optimization problems.

April 3, 2019View

Efficient Large-Scale Multiobjective Optimization Based on a Competitive Swarm Optimizer

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To develop an efficient competitive swarm optimizer-based search algorithm with a novel particle updating strategy to solve large-scale multiobjective optimization problems.
Formulated a competitive swarm optimizer incorporating a novel two-stage position updating strategy to improve search efficiency without relying on decision variable division.
Tested algorithmic performance on a suite of large-scale benchmark multiobjective optimization problems alongside an engineering application example.
Compared performance against state-of-the-art multiobjective evolutionary algorithms, including problem transformation, decision variable clustering, particle swarm optimization, and estimation of distribution approaches.
Demonstrated superior search efficiency and solution quality relative to all evaluated state-of-the-art multiobjective algorithms on benchmark problem landscapes.
Successfully bypassed the inaccuracies and computational overhead associated with conventional decision variable division methods on complex landscapes and applied problems.

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Implication

Simulation study demonstrates superior search efficiency of a competitive swarm optimizer in large-scale multiobjective problems, highlighting improved scalability in complex landscapes.

Cite This Study

Tian et al. (2019) studied this question.

synapsesocial.com/papers/6a1e09e1a3f4c58cc935366c https://doi.org/10.1109/tcyb.2019.2906383

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Implication

Simulation study demonstrates superior search efficiency of a competitive swarm optimizer in large-scale multiobjective problems, highlighting improved scalability in complex landscapes.

Efficient Large-Scale Multiobjective Optimization Based on a Competitive Swarm Optimizer

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Discussion

Implication

Cite This Study

Efficient Large-Scale Multiobjective Optimization Based on a Competitive Swarm Optimizer

Key Points

Discussion

Implication

Cite This Study

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