IGD Values Under Different Strategies: Multi-Objective Algorithm Benchmark Results

IGD Values Under Different Strategies is a 5.5 KB dataset by Wei Jiang, last updated in April 2026. It contains experimental results comparing an improved NSGAII algorithm (IM-NSGAII) against five other algorithms on ZDT, DTLZ, MaF, and WFG benchmark problems. The data likely contains Inverted Generational Distance (IGD) values used to evaluate algorithm performance in terms of convergence speed and population diversity.

Use Cases

• Benchmarking algorithm performance based on convergence speed and diversity metrics.
• Comparing the proposed IM-NSGAII algorithm against established methods based on reported IGD values.
• Analyzing the impact of specific algorithmic improvements like population evaluation and sparse population strategies on performance.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Explicitly compares six algorithms across four established benchmark suites.
• Released under a permissive CC-BY-4.0 license for reuse.

Limitations

• Row count and column definitions are unknown, requiring manual inspection after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Wei Jiang via figshare.

Collection Method

Experimental results from algorithm benchmarking.

Time Range

Benchmark results likely from a specific study period, but exact temporal coverage is not stated.

Freshness

Last updated 2026-04-17 17:36:11; freshness should be verified.

Geography

Spatial coverage is not applicable for algorithmic benchmark data.