GSA: Scheduling and allocation using genetic algorithm

This paper describes a unique approach to scheduling and allocation problem in high-level synthesis using genetic algorithm (GA). This approach is different from a previous attempt using GA in many respects. Our contributions include: a new chromosomal representation for scheduling and two subproblems of allocation; and two novel crossover operators to generate legal schedules. The approach has been tested on various benchmarks and results are compared with those obtained by other approaches such as simulated evolution, tabu search, HAL, SALSA II, STAR, etc.