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Solving the Order Batching Problem in Warehouses using Genetic Algorithms [Solución del Problema de Conformación de Lotes en Almacenes utilizando Algoritmos Genéticos]

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Cano J.A.
Correa-Espinal A.A.
Gómez-Montoya R.A.
TY - GEN T1 - Solving the Order Batching Problem in Warehouses using Genetic Algorithms [Solución del Problema de Conformación de Lotes en Almacenes utilizando Algoritmos Genéticos] AU - Cano J.A. AU - Correa-Espinal A.A. AU - Gómez-Montoya R.A. UR - http://hdl.handle.net/11407/6163 PB - Centro de Informacion Tecnologica AB - This article aims to develop a genetic algorithm to minimize the distance traveled in warehouses and distribution centers where the order-batching problem applies for order picking systems. For this, a new representation of solutions is proposed, in which each gene of a chromosome represents a customer order to be retrieved, easing the application of crossover and mutation operators. Through computational experiments, it is shown that the genetic algorithm generates significant savings in distance traveled and number of batches compared to a basic rule of order batch formation, especially in scenarios where a greater number of batches is required. We conclude that the genetic algorithm provides efficient solutions in a reasonable computational time, thus its implementation is highly recommended in operative environments of warehouses and distribution centers. © Centro de Informacion Tecnologica. All rights reserved. ER - @misc{11407_6163, author = {Cano J.A. and Correa-Espinal A.A. and Gómez-Montoya R.A.}, title = {Solving the Order Batching Problem in Warehouses using Genetic Algorithms [Solución del Problema de Conformación de Lotes en Almacenes utilizando Algoritmos Genéticos]}, year = {}, abstract = {This article aims to develop a genetic algorithm to minimize the distance traveled in warehouses and distribution centers where the order-batching problem applies for order picking systems. For this, a new representation of solutions is proposed, in which each gene of a chromosome represents a customer order to be retrieved, easing the application of crossover and mutation operators. Through computational experiments, it is shown that the genetic algorithm generates significant savings in distance traveled and number of batches compared to a basic rule of order batch formation, especially in scenarios where a greater number of batches is required. We conclude that the genetic algorithm provides efficient solutions in a reasonable computational time, thus its implementation is highly recommended in operative environments of warehouses and distribution centers. © Centro de Informacion Tecnologica. All rights reserved.}, url = {http://hdl.handle.net/11407/6163} }RT Generic T1 Solving the Order Batching Problem in Warehouses using Genetic Algorithms [Solución del Problema de Conformación de Lotes en Almacenes utilizando Algoritmos Genéticos] A1 Cano J.A. A1 Correa-Espinal A.A. A1 Gómez-Montoya R.A. LK http://hdl.handle.net/11407/6163 PB Centro de Informacion Tecnologica AB This article aims to develop a genetic algorithm to minimize the distance traveled in warehouses and distribution centers where the order-batching problem applies for order picking systems. For this, a new representation of solutions is proposed, in which each gene of a chromosome represents a customer order to be retrieved, easing the application of crossover and mutation operators. Through computational experiments, it is shown that the genetic algorithm generates significant savings in distance traveled and number of batches compared to a basic rule of order batch formation, especially in scenarios where a greater number of batches is required. We conclude that the genetic algorithm provides efficient solutions in a reasonable computational time, thus its implementation is highly recommended in operative environments of warehouses and distribution centers. © Centro de Informacion Tecnologica. All rights reserved. OL Spanish (121)
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Abstract
This article aims to develop a genetic algorithm to minimize the distance traveled in warehouses and distribution centers where the order-batching problem applies for order picking systems. For this, a new representation of solutions is proposed, in which each gene of a chromosome represents a customer order to be retrieved, easing the application of crossover and mutation operators. Through computational experiments, it is shown that the genetic algorithm generates significant savings in distance traveled and number of batches compared to a basic rule of order batch formation, especially in scenarios where a greater number of batches is required. We conclude that the genetic algorithm provides efficient solutions in a reasonable computational time, thus its implementation is highly recommended in operative environments of warehouses and distribution centers. © Centro de Informacion Tecnologica. All rights reserved.
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http://hdl.handle.net/11407/6163
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