Data-driven location–allocation for clean cooking LPG supply chains: A mixed-integer programming approach for Rwanda

doi:10.1016/j.esd.2026.101947

Data-driven location–allocation for clean cooking LPG supply chains: A mixed-integer programming approach for Rwanda

2026-02-04

0

PRE

AI

Z

Zeynep Goze Gurkan

P

Pablo Duenas-Martinez

A

Ayse Selin Kocaman *

DOI：10.1016/j.esd.2026.101947

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Abstract

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• MILP model designs nationwide clean-cooking LPG distribution networks. • Rooftop-level demand for 3.3M homes enables granular infrastructure planning. • Clustering approach improves retailer siting fairness and reduces system cost. • Model evaluates scalability under rising LPG demand and fuel price changes. • Datadriven planning supports equitable access to clean-cooking solutions.

Keywords:

LPG distribution

clean cooking

mixed-integer programming

retailer siting

data-driven planning

Data-driven location–allocation for clean cooking LPG supply chains: A mixed-integer programming approach for Rwanda

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