A Comparative Study of Simulated Annealing and Self-Organising Map Batching for Solving the Order Batching Problem in Warehouses

Abstract: Warehouses need efficient picking strategies. Batching orders is one such strategy, but creating efficient batches out of orders is computationally hard. We compare two algorithms to find approximate solutions to the batching problem; the general global optimisation algorithm Simulated Annealing and the batching specific algorithm Self-Organising Map Batching (SOMB). The results demonstrate that for a small number of orders, Simulated Annealing performs better than SOMB, but takes longer to run. For a large number of orders, SOMB performs better than Simulated Annealing and generates the result quicker. Which algorithm is the best at batching orders depends on the number of orders that are being batched.