Abstract

Simulated annealing (SA) is considered a valuable stochastic technique for resolving difficulties associated with comprehensive multidimensional optimisation, which guarantees optimal global convergence. This study explores the use of SA to address the challenges of redesigning warehouse networks and relates the effectiveness of three (3) diverse SA cooling schedules, namely; the basic geometric, logarithmic, and linear. The broad computational findings performed and described in the study indicate that the geometric cooling schedule generates consistent, superior quality, and timely solutions compared to the other schemes.

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