This study aims to develop a multi-objective version of the search group algorithm (SGA) called the multi-objective search group algorithm (MOSGA) to help determine thermo-economic optimization of flat-plate solar collector (FPSC) systems. Search mechanisms of the SGA were modified to determine non-dominated solutions through mutation, generation, and selection stages. Authors also mined the Pareto archive with a selection mechanism to maintain and intensify convergence and distribution of solutions. The study tested the proposed MOSGA with well-known multi-objective benchmark problems. Results were compared with outcomes from conventional algorithms using the same performance metrics to validate the capability and performance of the MOSGA. Afterward, MOSGA was applied to find the best design parameters to simultaneously optimize thermal efficiency and the total annual cost of FPSC systems. Four case studies were conducted with four different working fluids (pure water, SiO₂, Al₂O_3, and CuO nanofluids). Optimization results obtained by the MOSGA were analyzed and compared with solutions provided by other algorithms. The findings revealed relative improvement in thermal efficiency and reduced annual cost for all nanofluids compared to pure water. Thermal efficiency was improved by 2.2748%, 2.4298%, and 2.7948% for SiO₂, Al₂O_3, and CuO case studies, respectively, compared to pure water. Meanwhile, TAC rates were increased by 2.4111%, 2.3403%, and 2.9133% for these case studies, respectively. Comparative results also demonstrated that MOGSA was robustly effective and superior in the selection of appropriate design parameters of FPSC systems.

这项研究旨在开发称为多目标搜索组算法（MOSGA）的多目标版本的搜索组算法（SGA），以帮助确定平板太阳能收集器（FPSC）系统的热经济性优化。修改了SGA的搜索机制，以通过突变，生成和选择阶段来确定非主导解决方案。作者还使用选择机制开采了Pareto档案，以维护和加强解决方案的融合和分配。该研究对提出的MOSGA进行了著名的多目标基准测试。使用相同的性能指标将结果与常规算法的结果进行比较，以验证MOSGA的功能和性能。之后，应用MOSGA来寻找最佳设计参数，以同时优化FPSC系统的热效率和年度总成本。使用四种不同的工作液（纯水，SiO 2₂，Al ₂ O ₃和CuO纳米流体）。分析了由MOSGA获得的优化结果，并将其与其他算法提供的解决方案进行了比较。研究结果表明，与纯水相比，所有纳米流体的热效率都得到了相对改善，并降低了年成本。与纯水相比，SiO ₂，Al ₂ O ₃和CuO案例研究的热效率分别提高了2.2748％，2.4298％和2.7948％。同时，这些案例研究的TAC率分别提高了2.4111％，2.3403％和2.9133％。比较结果还表明，MOGSA在选择FPSC系统的适当设计参数方面具有强大的有效性和优越性。