All research
Optimization for Smallholder Farmers
Linear and multi-objective (NSGA-II) optimization balancing cost-effectiveness and nutrition.
Applied linear and multi-objective optimization, using SciPy and NSGA-II in pymoo, to decisions facing smallholder farmers. Solutions are ranked by cost-effectiveness and nutritional balance, giving a Pareto front of trade-offs rather than a single answer.
This work connects to our studies of farmer resilience in Senegal and of soft-computing methods for climate adaptation.
Publications
- FES Journal
Unveiling the resilience of smallholder farmers in Senegal amidst extreme climate conditions
Food and Energy Security, 13(1), e523 · 2024
@article{moller2024unveiling, title = {Unveiling the resilience of smallholder farmers in Senegal amidst extreme climate conditions}, author = {Moller, Kieron and Nejadhashemi, A. Pouyan and Talha, Muhammad}, journal = {Food and Energy Security}, volume = {13}, number = {1}, pages = {e523}, year = {2024}, publisher = {Wiley}, doi = {10.1002/fes3.523} }
- Heliyon Journal
Soft computing paradigm for climate change adaptation and mitigation in Iran, Pakistan, and Turkey: A systematic review
Heliyon, 11(2), e41974 · 2025
@article{talha2025soft, title = {Soft computing paradigm for climate change adaptation and mitigation in Iran, Pakistan, and Turkey: A systematic review}, author = {Talha, Muhammad and Nejadhashemi, A. Pouyan and Moller, Kieron}, journal = {Heliyon}, volume = {11}, number = {2}, pages = {e41974}, year = {2025}, publisher = {Elsevier}, doi = {10.1016/j.heliyon.2025.e41974} }
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