Conceptual Framework for Adaptive Bacterial Memetic Algorithm Parameterization in Storage Location Assignment Problem

Kitti Udvardy, Polina Görbe, Tamás Bódis and János Botzheim ()
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Kitti Udvardy: Multidisciplinary Doctoral School of Engineering, Széchenyi University, 9026 Győr, Hungary
Polina Görbe: Department of Logistics and Forwarding, Széchenyi University, 9026 Győr, Hungary
Tamás Bódis: Department of Logistics and Forwarding, Széchenyi University, 9026 Győr, Hungary
János Botzheim: Department of Artificial Intelligence, Faculty of Informatics, ELTE Eötvös Loránd University, 1117 Budapest, Hungary

Mathematics, 2024, vol. 12, issue 23, 1-16

Abstract: Recognized as an NP-hard combinatorial challenge, Storage Location Assignment Problem (SLAP) demands heuristic or algorithmic solutions for effective optimization. This paper specifically examines the enhancement of SLAP through the utilization of evolutionary algorithms, as they are particularly suitable for complex cases. Among others, the genetic algorithm (GA) is typically applied to solve this problem. This paper investigates the Bacterial Memetic Algorithm (BMA) as a possible solution for optimization. Though the comparative analysis of the BMA with the previously well-used GA algorithm under certain test parameters reveals that BMA is suitable for SLA optimization, BMA failed to achieve better results. We attribute the unsatisfactory results to the parameter settings, as illustrated by a few specific examples. However, the complexity of the problem and the parameterization does not allow for continuous manual parameter adjustment, which is why we have identified the need for a concept that automatically and adaptively adjusts the parameter settings based on the statistics and fitness values obtained during the execution. The novelty of this paper is to specify the concept of adaptive BMA parameterization and rules.

Keywords: storage location assignment problem; bacterial memetic algorithm; adaptive parameterization; evolutionary algorithms (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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