Resumen
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.
Título traducido de la contribución | Solving the Order Batching Problem in Warehouses using Genetic Algorithms |
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Idioma original | Español |
Páginas (desde-hasta) | 235-244 |
Número de páginas | 10 |
Publicación | Informacion Tecnologica |
Volumen | 29 |
N.º | 6 |
DOI | |
Estado | Publicada - dic. 2018 |
Palabras clave
- Genetic algorithms
- Metaheuristics
- Order batching
- Order picking
- Warehouse management
Tipos de productos de Minciencias
- Artículo B - Q3