An Order Batching Method Based on GGA in a Picker-To-Part System with the Travel Routing Policy  
Author Jason Chao-Hsien Pan

 
Co-Author(s) Po-Hsun Shih

 
Abstract Order batching policy decides the way to combine different orders to form a batch. It is known that the order batching, orders with similar picking location are integrated into a batch and picked in one picking tour, can reduce the total travel distance required for all orders and enhance the operational efficiency in a picker-to-part system. Since batching is a NP-hard problem, this paper proposes an approach based on group genetic algorithm (GGA) for the routing policy of traversal. In addition, a measurement is presented to evaluate the similarity of a batch with the feature of the traversal routing policy. A crossover operator, namely eugenic mating, and a re-grouped mechanism are developed on the basis of similarity measures to attain a better solution for the order batching problem. To verity the efficiency of the heuristic, the proposed heuristic algorithm is compared with other existing algorithms through computer simulation and the result indicates that the proposed method generates better solutions.

 
Keywords Order picking method, Order batching, Group Genetic algorithms, Warehouses system, Operation research
   
    Article #:  2094
 
Proceedings of the 20th ISSAT International Conference on Reliability and Quality in Design
August 7-9, 2014 - Seattle, Washington, U.S.A.