1. Market price layer
The analytical system uses agricultural market-price observations to identify potential price differentials between market pairs.
Project 1 · Methodology
A reproducible analytical framework for graph-based combinatorial optimization of agricultural supply networks in Burundi.
Research design
The analytical system uses agricultural market-price observations to identify potential price differentials between market pairs.
OpenStreetMap road data are transformed into a routable analytical network and used to estimate road distance between market nodes.
Ordered origin-destination pairs are evaluated using gross price gaps and transport-cost scenarios.
Linear programming is used to maximize normalized net margins subject to product-level supply, demand and shared-corridor constraints.
Candidate routes are evaluated across multiple transport-cost scenarios to distinguish robust, strong, moderate and sensitive opportunities.
Corridor-level indicators combine robustness, product breadth, optimization persistence and spatial efficiency to produce a research-priority hierarchy.
Optimization model
The core allocation problem is solved with linear programming. Decision variables represent normalized flows on profitable product-specific origin-destination arcs.
Constraints include normalized origin supply limits, destination demand limits and shared corridor-capacity scenarios. The objective is to maximize total normalized net margin after transport costs.
Reproducibility
The project records data preparation, network construction, optimization, sensitivity analysis, corridor prioritization, validation checks and research limitations as separate stages.
All normalized optimization quantities are analytical units and should not be interpreted as observed tonnes or transaction volumes.
Scientific status