Abstract
The optimization function of simulated annealing (SA) and temperature parallel SA (parallel tempering (PT)) is studied in solving the quadratic assignment problems (QAPs). The experimental analyses are performed in the same manner as for the traveling salesman problems (TSPs). As similar to the case of TSP, the optimization performance of SA is maximized by the intensive search at some intermediate temperature and at this effective temperature, downward inter basin transition dynamics last until the end of the search time. The performance of PT also depends on the search in some intermediate temperature range; however, the role of the effective temperature is unclear compared to the case of TSP.
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