<![CDATA[In recent years, the concept of smart cities and infrastructure has gained momentum as a solution to challenges such as population growth, resource management, and environmental sustainability. Rapid urbanization in many developing countries highlights the need for efficient infrastructure planning and management. This framework offers a structured approach for decision-making and resource allocation, enabling prioritization of investments to maximize limited resources while supporting development goals. The framework is tested through an analysis of the Smart Street Lighting Systems (SSLS) in Surabaya, Indonesia, addressing the city's intention to upgrade street lighting to reduce maintenance costs and energy consumption. Currently, the street lighting system faces issues including a high rate of broken or damaged lights and inefficiencies in handling complaints. However, limited funding and varied regional needs constrain any comprehensive upgrade. The proposed framework integrates the Analytical Hierarchy Process (AHP) to prioritize regions as weighting inputs, Mixed Integer Goal Programming (MIGP) to optimize the distribution of SSLS and conventional LED lighting across regions, and Cost-Benefit Analysis (CBA) to evaluate financial feasibility. Results recommend purchasing 11,915 new SSLS units with region-specific distributions, achieving a financially viable Benefit-Cost Ratio (BCR) of 2.059. These findings demonstrate practical implementation of smart city principles, balancing cost-efficiency, service performance, and stakeholder priorities. Policymakers can use this framework to maximize impact within budget constraints. This framework serves as a viable template for other regions and countries embarking on smart city infrastructure implementation.]]>
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