The sizes of the metal-oxide-semiconductor (MOS) transistors in an operational amplifier must guarantee strong direct current operating point (DCOP) conditions. This paper shows the usefulness of two population-based optimization algorithms to size transistors, namely—particle swarm optimization (PSO) and many optimizing liaisons (MOL). Both optimization algorithms link the circuit simulator SPICE to measure electrical characteristics. However, SPICE provides an output-file indicating that a transistor is in strong inversion but the DCOP can be in the limit, and it can switch to a different condition. In this manner, we highlight the application of PSO and MOL to size operational transconductance amplifiers (OTAs), which DCOP conditions are improved by the introduction of a procedure that handles constraints to ensure that the transistors are in the appropriate DCOP. The Miller and RFC-OTA are the cases of study, and their sizing is performed using UMC 180 nm CMOS technology. In both OTAs, the objective function is the maximization of the gain-bandwidth product under the main constraint of guaranteeing DCOPs to improve two figures of merit and to provide robustness to Monte Carlo simulations and PVT variations.