Figures Data for Multi-Objective Evolutionary Algorithm Benchmarking

Wei Jiang's dataset contains experimental figures and data used to evaluate an improved NSGAII algorithm (IM-NSGAII) against five other algorithms. The data covers performance on ZDT, DTLZ, MaF, and WFG benchmark problems, focusing on convergence speed and population diversity. The dataset was last updated on April 17, 2026.

Use Cases

• Benchmarking algorithm performance based on convergence speed and population diversity metrics
• Comparing the proposed IM-NSGAII algorithm against other algorithms on standard test problems
• Analyzing the impact of population evaluation and sparse population strategies on algorithm behavior
• Validating improvements in diversity maintenance for complex Pareto fronts

Strengths

• Data is derived from experiments on four established benchmark suites (ZDT, DTLZ, MaF, WFG)
• Includes comparative results against five widely used algorithms
• Released under a permissive CC-BY-4.0 license
• Dataset size is 26.6 MB, indicating a non-trivial volume of results

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

figshare

Collection Method

Experimental results from algorithm benchmarking

Time Range

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Freshness

Last updated 2026-04-17 17:36:03; freshness should be verified

Geography

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