Temperature parallel simulated annealing (TPSA) was applied to in-core fuel management optimizations, and the optimization performance was evaluated by comparing TPSA with traditional simulated annealing (SA). The TPSA method is an optimization algorithm that is based on SA, but has several distinguishing features: an automatic temperature annealing schedule, time homogeneity, and a significant affinity with parallel execution. The calculation results of a test problem revealed that TPSA was superior to traditional SA in terms of detailed loading pattern optimizations. The reason for this is that the TPSA temperature annealing schedule can effectively avoid local optima by repeating a cooling and heating cycle automatically.