Solving Hospital Layout Problem as Quadratic Assignment Problem by Marine Predators Algorithm

The problem of determining the location of the hospital's department to minimize the total distance traveled by patients can be formulated as a Quadratic assignment problem (QAP), one of the most difficult and important NP-hard problems in logistics. In this paper, we will solve the hospital layout problem using a swarm intelligence metaheuristic that mimics the behavior of marine predators in search of their prey called marine predator algorithm (MPA). We do a comparison study between MPA and other metaheuristics from different categories including math-based (SHIO), human-based (WarSO), evolutionary-based (DE), and biology-based (BBOA) using a benchmark dataset “Nug-12” instance from QAPLIB to assess its suitability for this specific application. The results show that MPA could solve hospital layout problems and appear superior in achieving the best solution within a feasible time.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/miucc62295.2024.10783568
Citations
1
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.35
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article

Solving Hospital Layout Problem as Quadratic Assignment Problem by Marine Predators Algorithm

Mohamed Ghoneimy, Mohammad E. Moftah
1 citations
Advanced Manufacturing and Logistics Optimization
0.35
article

Solving Hospital Layout Problem as Quadratic Assignment Problem by Marine Predators Algorithm

Mohamed Ghoneimy, Mohammad E. Moftah
article en
1 citations

Abstract

The problem of determining the location of the hospital's department to minimize the total distance traveled by patients can be formulated as a Quadratic assignment problem (QAP), one of the most difficult and important NP-hard problems in logistics. In this paper, we will solve the hospital layout problem using a swarm intelligence metaheuristic that mimics the behavior of marine predators in search of their prey called marine predator algorithm (MPA). We do a comparison study between MPA and other metaheuristics from different categories including math-based (SHIO), human-based (WarSO), evolutionary-based (DE), and biology-based (BBOA) using a benchmark dataset “Nug-12” instance from QAPLIB to assess its suitability for this specific application. The results show that MPA could solve hospital layout problems and appear superior in achieving the best solution within a feasible time.

October University of Modern Sciences and Arts (EG)
Life below water
Openalex Percentile: Top 32%
Advanced Manufacturing and Logistics Optimization
0.35
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