Research on optimization problem of the automated warehouse using an improved ant colony algorithm

Ant colony algorithm has great ability of searching better solution, there are some shortcomings such as tending to go into stagnation behavior and needing long computing time. Based on the algorithm, we analyzed the working characteristics of the fixed storage racks in automated warehouse. Optimize the order picking strategies to improve the throughput of the entire warehouse. According to the requirements of order picking tasks in single aisle rack, a mathematic model was constructed with multiple constraints and the aim of minimum the travel time. A novel fast improved ant colony algorithm for the order picking problem was designed. Three improvements were adopted: awaiting nodes set, selection operator and dynamic change on algorithm parameters. Computational simulations were carried to validate the approach. The test results demonstrate the improved algorithm has better overall search ability and quickly astringency, satisfying the demands of medium or large scale work.