Agricultural Wholesale Market Location Selection Framework

A case study evaluates seven candidate location schemes for large-scale Agricultural Product Wholesale Markets (APWMs). The dataset supports a five-phase methodology integrating GIS data, AHP, and entropy weight methods for site selection. Guizhe Xin authored this research, which was last updated in April 2026.

Use Cases

• Rank candidate APWM locations using criteria like location, planning, and transportation scores.
• Optimize subjective and objective weight integration for site selection using the documented Genetic Algorithm (GA) approach.
• Analyze the correlation between national territorial planning data and urban compatibility metrics for infrastructure siting.
• Validate location selection outcomes against road traffic planning and industrial development planning layers in a GIS.

Strengths

• Framework integrates five key evaluation criteria: location, planning, transportation, land use, and urban compatibility.
• Methodology validated through a case study comparing seven candidate location schemes.
• Data consolidates national spatial planning, road traffic planning, and urban big data into a unified database.

Limitations

• The dataset is very small at 9.5 KB, indicating limited raw observational data or a summary of model outputs.
• Specific row counts, column names, and sample data are unavailable, limiting direct analysis.
• The case study's geographic scope and temporal coverage are not specified, reducing generalizability.

Provenance

Source

Guizhe Xin via figshare.

Collection Method

Proposed framework integrates GIS technology, Analytic Hierarchy Process (AHP), entropy weight method, and a Genetic Algorithm implemented in Python.

Freshness

Last updated in April 2026.