A multi-objective framework for efficient policy configurations: balancing military expenditure, human development, and peace in South America

Introduction Development, peace, and security are fundamental pillars of public policy, particularly in developing countries where resource constraints and governance challenges require strategic prioritization. Given the interdependent nature of these domains, there is a need for analytical frameworks capable of identifying efficient trade-offs among competing policy objectives. Methods This study develops a multi-objective optimization (MOOP) model that simultaneously incorporates military expenditure (ME), the Human Development Index (HDI), and the Global Peace Index (GPI) as objective functions. The model includes decision variables representing key state sectors, including education, research and development, taxation, globalization, infrastructure, and technology. Using panel data from ten South American countries covering the period 2008–2016, the MOOP approach generates a Pareto-efficient set of policy solutions. Results The results reveal balanced and feasible trade-offs among development, peace, and security objectives. Optimal policy configurations are generally associated with improvements in education, technological adoption, globalization indicators, and economic capacity. These factors contribute simultaneously to higher levels of human development and peace while maintaining sustainable levels of military expenditure. Discussion and conclusions This study extends the application of MOOP to national-level policy analysis and provides country-specific efficiency benchmarks that can support policymakers in designing coherent development, peace, and security strategies. The findings demonstrate the usefulness of frontier-based optimization as a decision-support tool for integrated public policy design in complex and resource-constrained environments.