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The Use of a Genetic Algorithm for Sorting Warehouse Optimisation
by
Dulina, Ľuboslav
, Mozol, Štefan
, Krajčovič, Martin
, Danilczuk, Wojciech
, Burganová, Natália
, Furmannová, Beáta
, Svitek, Radovan
, Grznár, Patrik
, Gola, Arkadiusz
, Plinta, Dariusz
in
Algorithms
/ Business process management
/ Computer programs
/ Genetic algorithms
/ Heuristic methods
/ Mutation
/ Optimization
/ Shipments
/ Simulation
/ Software
/ Sorting algorithms
/ Warehouses
/ Workers
2021
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The Use of a Genetic Algorithm for Sorting Warehouse Optimisation
by
Dulina, Ľuboslav
, Mozol, Štefan
, Krajčovič, Martin
, Danilczuk, Wojciech
, Burganová, Natália
, Furmannová, Beáta
, Svitek, Radovan
, Grznár, Patrik
, Gola, Arkadiusz
, Plinta, Dariusz
in
Algorithms
/ Business process management
/ Computer programs
/ Genetic algorithms
/ Heuristic methods
/ Mutation
/ Optimization
/ Shipments
/ Simulation
/ Software
/ Sorting algorithms
/ Warehouses
/ Workers
2021
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Do you wish to request the book?
The Use of a Genetic Algorithm for Sorting Warehouse Optimisation
by
Dulina, Ľuboslav
, Mozol, Štefan
, Krajčovič, Martin
, Danilczuk, Wojciech
, Burganová, Natália
, Furmannová, Beáta
, Svitek, Radovan
, Grznár, Patrik
, Gola, Arkadiusz
, Plinta, Dariusz
in
Algorithms
/ Business process management
/ Computer programs
/ Genetic algorithms
/ Heuristic methods
/ Mutation
/ Optimization
/ Shipments
/ Simulation
/ Software
/ Sorting algorithms
/ Warehouses
/ Workers
2021
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The Use of a Genetic Algorithm for Sorting Warehouse Optimisation
Journal Article
The Use of a Genetic Algorithm for Sorting Warehouse Optimisation
2021
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Overview
In the last decade, simulation software as a tool for managing and controlling business processes has received a lot of attention. Many of the new software features allow businesses to achieve better quality results using optimisation, such as genetic algorithms. This article describes the use of modelling and simulation in shipment and sorting processes that are optimised by a genetic algorithm’s involvement. The designed algorithm and simulation model focuses on optimising the duration of shipment processing times and numbers of workers. The commercially available software Tecnomatix Plant Simulation, paired with a genetic algorithm, was used for optimisation, decreasing time durations, and thus selecting the most suitable solution for defined inputs. This method has produced better results in comparison to the classical heuristic methods and, furthermore, is not as time consuming. This article, at its core, describes the algorithm used to determine the optimal number of workers in sorting warehouses with the results of its application. The final part of this article contains an evaluation of this proposal compared to the original methods, and highlights what benefits result from such changes. The major purpose of this research is to determine the number of workers needed to speed up the departure of shipments and optimise the workload of workers.
Publisher
MDPI AG
Subject
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