NONE 20260722093113421 wseas/wseas content-registration-form@crossref.org content-registration-form International Journal of Environmental Engineering and Development 2945-1159 Harrison Obiora Amuji Department of Statistics Federal University of Technology Owerri Imo State NIGERIA Donatus E. Onwuegbuchunam Department of Maritime Science and Technology Federal University of Technology Owerri, Imo State NIGERIA Kenneth U. Nnadi Department of Maritime Science and Technology Federal University of Technology Owerri, Imo State NIGERIA Asuquo O. Bassey Department of Maritime Science Rivers State University Port-Harcourt, Rivers State NIGERIA Abdulmalik M. Mustapha Department of Transport Management Ibrahim Badamasi Babangida University Lapai, Niger State, NIGERIA Louisa N. Amaechi Directorate of General Studies Federal University of Technology Owerri, Imo State NIGERIA Kenneth O. Okeke Department of Maritime Science and Technology Federal University of Technology Owerri, Imo State NIGERIA Elochukwu Emefo Department of Supply Chain Management Federal University of Technology Owerri, Imo State NIGERIA This paper presents an optimization model for the equitable and cost-effective allocation of relief materials to internally displaced persons (IDP) camps in Abuja, Nigeria. Due to the inherent challenges of humanitarian logistics, including data uncertainty and complex supply chains, this study employs a robust linear programming–geometric programming (LP–GP) hybrid model to determine the optimal monthly distribution cost from available semi-annual budgets. The LP–GP hybrid model offers a significant advantage over traditional linear programming by providing a globally optimal solution even when initial budget data may be inflated or unreliable, thereby addressing a critical challenge in humanitarian contexts such as financial leakages. Using data from five IDP camps for the first half of 2024, sourced from the National Emergency Management Agency (NEMA) and inter-agency registration exercises, the study identifies an optimal monthly distribution cost of ₦62,932,233 (approximately ₦377.6 million semi-annually), representing a 95.3% reduction relative to the allocated budget of ₦8.01 billion. The robustness of the model is examined under varying input parameters, confirming the independence of the optimal cost from the potentially inflated allocated budget. The findings highlight substantial potential for improved efficiency and resource management through the adoption of a data- driven, harmonized distribution system. 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