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An Estimation of Distribution Algorithm-Based Approach for the Order Batching Problem: An Experimental Study
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Author(s): Ricardo Pérez-Rodríguez (Center for Research in Mathematics, Mexico)and Arturo Hernández-Aguirre (Center for Research in Mathematics, Mexico)
Copyright: 2016
Pages: 10
Source title:
Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations
Source Author(s)/Editor(s): Alberto Ochoa-Zezzatti (Juarez City University, Mexico), Jöns Sánchez (Consejo Nacional De Ciencie Y Tecnologia (CONACYT), Mexico), Miguel Gastón Cedillo-Campos (Transportation Systems and Logistics National Laboratory, Mexican Institute of Transportation, Mexico)and Margain de Lourdes (Polytechnic University of Aguascalientes, Mexico)
DOI: 10.4018/978-1-4666-9779-9.ch026
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Abstract
In the supply chain and the planning and control of warehouse processes, the order picking is an aspect critical. Combining customer orders into picking orders to minimize the picking time is known such order batching. Extensive evolutionary algorithms haven been proposed to build better batches for the order picking. The authors think that any algorithm should preserve batches that appear frequently in all members of the population in order to keep track and inherit these characteristics exhibited by the parents to the next generation. However, the traditional evolutionary operators used in current research sometimes lose the characteristics mentioned. In order to describe the characteristics exhibited by the parents as a distribution of the solution space, the authors build a probability model. An acceptable performance using the model proposed is shown against different evolutionary algorithms known in the literature in a series of extensive numerical experiments.
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