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This paper compares three heuristic search algorithms: genetic algorithm (GA), simulated annealing (SA) and tabu search (TS), for hardware–software partitioning. The algorithms operate on functional blocks for designs represented as directed acyclic graphs, with the objective of minimising processing time under various hardware area constraints. Thecomparison involves a model for calculating processing time based on a non-increasing first-fit algorithm to schedule tasks, given that shared resource conflicts do not occur. The results show that TS is superior to SA and GA in terms of both search time and quality of solutions. In addition, we have implemented an intensification strategy in TS called penalty reward, which can further improve the quality of results.