Evolutionary computation presents a new paradigm shift in hardware design and synthesis. According to this paradigm, hardware design is pursued by deriving inspiration from biological organism. Instead of using human made models and techniques, the new methodology employs search heuristics to develop efficient designs. In this thesis, a multiobjective optimization for evolutionary logic design based on Ant Colony optimization algorithm is proposed. The result obtained using the proposed algorithms are compared to those obtained using existing evolutionary techniques as well as conventional techniques. Area, delay, and power consumption are used as performance measures based on which the proposed algorithms and the existing techniques are compared. It is shown that the designed circuits using the proposed algorithms outperform those of the existing techniques.