Task assignment by parallel simulated annealing

Simulated annealing for obtaining approximate solutions to combinatorial optimization problems is addressed. The serial algorithm, however, can require extensive computation time. Most parallel algorithms for simulated annealing are problem-specific and/or violate the serial decision sequence, thereby allowing errors not present in the serial algorithm. Maintaining the serial sequence is necessary to prove that the algorithm converges to a global optimum solution when allowed to reach equilibrium at each temperature. A parallel algorithm which is both problem-independent and maintains the serial decision sequence is presented. The parallel algorithm uses the concurrency techniques of speculative computation to achieve speedup which can exceed log/sub 2/P, on P processors. For three problems investigated, the average speedup on eight processors was 2.6.<
>