Genetic Algorithm Weight Optimization Results for Agricultural Market Siting

5.5 KB of data contains the final weights from a genetic algorithm optimization process for agricultural wholesale market location selection. The dataset was created by Guizhe Xin and uploaded to figshare in April 2026. It supports a case study evaluating seven candidate location schemes.

Use Cases

• Analyze optimized comprehensive weights for location, planning, transportation, land use, and urban compatibility criteria.
• Validate the genetic algorithm's convergence results against initial AHP and entropy method weights.
• Compare the final quantitative rankings of the seven candidate location schemes from the case study.

Strengths

• Data integrates weights from AHP, entropy method, and genetic algorithm optimization.
• Case study framework evaluated five criteria across seven candidate schemes.

Limitations

• Dataset is only 5.5 KB, indicating very limited scope, likely containing only final summary results.
• No raw input data, intermediate calculations, or sample rows are provided for verification.

Provenance

Source

figshare, author Guizhe Xin.

Collection Method

Generated by a Python-implemented genetic algorithm to re-optimize combined subjective (AHP) and objective (entropy) weights.

Time Range

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Freshness

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Geography

Based on a case study likely in China, referencing national territorial planning.