Decision Variables for Cold Chain Pre-Cooling Network Optimization in Shandong, China

A 2026 study by Chen Ying proposes an integrated optimization framework for designing first-mile pre-cooling distribution center networks for fresh agricultural products. The dataset likely contains the decision variables and parameters for a multi-objective nonlinear model minimizing logistics cost and maximizing product freshness, incorporating stage-specific decay and carbon emissions. An empirical case study in Shandong Province, China, compares three pre-cooling scenarios.

Use Cases

• Benchmarking location-routing algorithms based on the described multi-objective nonlinear mathematical model.
• Analyzing trade-offs between logistics cost and product freshness in cold chain design based on the stage-specific freshness decay function.
• Evaluating environmental impact of cold chain strategies based on the incorporated transportation-related carbon emissions.
• Comparing centralized versus decentralized pre-cooling strategies for perishable agricultural supply chains.

Strengths

• Includes a stage-specific freshness decay function to better characterize perishability.
• Incorporates transportation-related carbon emissions for environmental relevance.
• Provides empirical results from a case study in Shandong Province, China, under three distinct scenarios.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating limited scope.

Provenance

Source

Chen Ying via figshare

Collection Method

Generated as part of a research study proposing an optimization framework.

Freshness

Last updated 2026-05-29 17:38:00; freshness should be verified.

Geography

Shandong Province, China