@inbook{8d11a908e02f4afcac02c53ce1ef10ac,
title = "Modified RK-EDA to Solve a Permutation-Based Spare Part Allocation Problem",
abstract = "This paper presents an application of evolutionary algorithms for a spares part allocation problem in the telecom industry. The aim is to have the right spare parts at the right time at the right place in order to improve the quality of the service offered by a telecom organization by maximizing its resource utilization, maximizing revenues, while minimizing the total cost. Previous work has investigated two evolutionary algorithms, a Random Key Estimation of Distribution Algorithm (RKEDA) and a Genetic Algorithm (GA) for this problem and reported a comparable performance for them. We present a modified RKEDA for this problem, compare its performance to previous results, and show further performance improvements that can be achieved.",
keywords = "Genetic algorithm, Resource management, RKEDA",
author = "Nouf Alkaabi and Siddhartha Shakya and Adriana Gabor and Lee, {Beum Seuk} and Gilbert Owusu",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2022",
doi = "10.1007/978-3-030-89698-0_33",
language = "British English",
series = "Lecture Notes on Data Engineering and Communications Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "310--318",
booktitle = "Lecture Notes on Data Engineering and Communications Technologies",
address = "Germany",
}