A Pipeline-Based Genetic Algorithm for Time-Critical Systems

This paper presents the Hyper Generation–Genetic Algorithm (HG-GA), a proposed pipelined architecture for evolutionary optimization in time-critical systems. The microarchitecture enables parallel chromosome processing across genetic operations ensuring deterministic timing and high throughput. The design exploits deep parallelism and resource reuse, minimizing idle cycles and maximizing genetic diversity. A proof-of-concept implementation demonstrates seamless progression from initialization to convergence, validating the architecture’s ability to accelerate solution convergence under strict timing constraints. Experimental results show convergence within 100 clock cycles and achieving high fitness thresholds in few cycles.