Improved arithmetic optimization algorithm for patient admission scheduling problem

The patient admission scheduling problem (PASP) has been studied for many years as one of the most important scheduling problems in the health sector. The primary goal of PASP is to assign patients to appropriate hospital beds while considering some hard and soft constraints. PASP is an NP-hard prob...

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Vydané v:Soft computing (Berlin, Germany) Ročník 28; číslo 7-8; s. 5853 - 5879
Hlavní autori: Alawad, Noor Aldeen, Abed-alguni, Bilal H., Saleh, Israa I.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2024
Springer Nature B.V
Predmet:
Algorithms
Arithmetic
Artificial Intelligence
Benchmarks
Comparative analysis
Computational Intelligence
Control
Decision making
Engineering
Genetic algorithms
Integer programming
Mathematical analysis
Mathematical Logic and Foundations
Mechatronics
Medical research
Operators (mathematics)
Optimization
Optimization algorithms
Parameter modification
Patients
Performance evaluation
Robotics
Scheduling
Strategic management
Island-based
Arithmetic optimization algorithm
Discrete optimization problems
PASP benchmark
Patient admission scheduling problem
ISSN:1432-7643, 1433-7479
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Shrnutí:The patient admission scheduling problem (PASP) has been studied for many years as one of the most important scheduling problems in the health sector. The primary goal of PASP is to assign patients to appropriate hospital beds while considering some hard and soft constraints. PASP is an NP-hard problem, which implies that the optimization approach is one of the best approaches that can be used to solve it. The arithmetic optimization algorithm (AOA) is a new optimization algorithm that can effectively solve both continuous and discrete optimization problems. However, it may suffer from poor exploration and premature convergence to sub-optimal solutions due to some problems with its exploration operators. In this paper, we propose a new method for the PASP using an improved AOA algorithm called the island-based AOA ( i AOA). The new algorithm is based on a structured population model called the island model. This model distributes the population of candidate solutions among islands that periodically exchange some of the candidate solutions among each other based on a migration protocol. In i AOA, some modifications were applied to AOA’s parameters to make it capable of handling discrete space. We evaluated i AOA using a public benchmark for the PASP and compared our results with those of other baseline algorithms (DFPA, SA, HS, GD-NLGD, HTS, TS, I-BBO, and MBBO). The simulation results revealed that i AOA achieved the minimum average execution time on 5 out of 6 instances of the public benchmark. It also showed that i AOA achieved the second minimum average violation of the objective function over 10 independent runs. Finally, the statistical examination of the experimental results using Friedman and Wilcoxon tests confirms the significance of the results of i AOA compared with the other baseline algorithms.
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-023-09470-5