Work

Multiobjective Optimization Based on Gene Expression Programming

Year: 2007

Type: article

Abstract: :Traditional Multiobjective Optimization Algorithms are inefficiency in high dimensional decision space. To solve this problem, a novel method named Multiobjective Optimization based on Gene Expression Programming (GEPMO) was proposed. The main contributions of this study include: proposing a new coding method for chromosome,designing some operators for the new coding,analyzing the size of coding space, and presenting the framework of GEPMO. Extensive experiment results on enhanced standard test functions showed that, GEPMO is feasible and effective. In high dimensional decision space，the result set of SPEA is covered by GEPMO at least 87.5%, inversely at most 5%.

Source: DOAJ (DOAJ: Directory of Open Access Journals)

Author: Shaojie Qiao

Language: English

Topic: Advanced Multi-Objective Optimization Algorithms

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2386525341

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