Optimization of Warehouse Operations with Genetic Algorithms
Mirosław Kordos, Jan Boryczko, Marcin Blachnik, Sławomir Golak
Applied Sciences, 2020, 10(14), 4817Abstract
We present a complete, fully automatic solution based on genetic algorithms for the
optimization of discrete product placement and of order picking routes in a warehouse. The solution
takes as input the warehouse structure and the list of orders and returns the optimized product
placement, which minimizes the sum of the order picking times. The order picking routes are
optimized mostly by genetic algorithms with multi-parent crossover operator, but for some cases
also permutations and local search methods can be used. The product placement is optimized by
another genetic algorithm, where the sum of the lengths of the optimized order picking routes is
used as the cost of the given product placement. We present several ideas, which improve and
accelerate the optimization, as the proper number of parents in crossover, the caching procedure,
multiple restart and order grouping.
Software (The software is newer than the paper and contains several new enhancements, which are not described in the paper.)