The Use of a Genetic Algorithm for Sorting Warehouse Optimisation

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 mo...

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Veröffentlicht in:Processes 2021-07, Vol.9 (7), p.1197
Hauptverfasser: Grznár, Patrik, Krajčovič, Martin, Gola, Arkadiusz, Dulina, Ľuboslav, Furmannová, Beáta, Mozol, Štefan, Plinta, Dariusz, Burganová, Natália, Danilczuk, Wojciech, Svitek, Radovan
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container_end_page
container_issue 7
container_start_page 1197
container_title Processes
container_volume 9
creator Grznár, Patrik
Krajčovič, Martin
Gola, Arkadiusz
Dulina, Ľuboslav
Furmannová, Beáta
Mozol, Štefan
Plinta, Dariusz
Burganová, Natália
Danilczuk, Wojciech
Svitek, Radovan
description 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.
doi_str_mv 10.3390/pr9071197
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source MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals
subjects Algorithms
Business process management
Computer programs
Genetic algorithms
Heuristic methods
Mutation
Optimization
Shipments
Simulation
Software
Sorting algorithms
Warehouses
Workers
title The Use of a Genetic Algorithm for Sorting Warehouse Optimisation
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