Simultaneous generation of heat, cooling, and other secondary products along with electricity can be more efficient than stand-alone production of these individual streams, due to the opportunities for process integration that naturally arise in such systems. Various cogeneration, trigeneration, and polygeneration schemes can also be configured to achieve operational flexibility to cope with a variable supply of fuels and feedstocks, as well as fluctuating product demand. However, techno-economic risks resulting from long-term uncertainties in the prices of both inputs and outputs can be a barrier to investing in these efficient systems. Hence, this chapter presents a target-oriented robust optimization (TORO) approach for dealing with parametric uncertainties in the synthesis of cogeneration, trigeneration, and polygeneration systems. The model is formulated as a mixed-integer nonlinear program (MINLP), and candidate designs at different levels of robustness can be assessed using Monte Carlo simulation. The methodology is illustrated with a case study on the synthesis of a cogeneration plant.