Increasing freshwater scarcity driven by population growth presents a complex planning and design challenge that requires balancing system performance with economic feasibility. While desalination offers a viable alternative to conventional water sources, design decisions for small scale renewable desalination systems are often made using single objective or performance driven criteria, limiting their practical applicability. This study formulates the design of a solar still desalination system integrated with a flat plate collector (DS-FP) as a multi-objective decision problem from an industrial engineering and operations management perspective. A MATLAB based numerical model is developed to quantify both thermal performance and total system cost under realistic operational constraints. The design problem is solved using a multi-objective imperialist competitive algorithm (MICA) to generate a Pareto optimal solution set that explicitly captures trade-offs between efficiency and cost. Rather than selecting a single optimal configuration, the resulting Pareto front provides a structured decision space that enables stakeholders to select designs aligned with specific budgetary and operational priorities. The optimized DS-FP configurations are benchmarked against published studies, demonstrating consistent improvements in both economic and performance indicators. The findings highlight the importance of multi-objective decision analysis in guiding cost effective and scalable deployment of solar desalination systems.