Amr AbdelAziz - Academia.edu (original) (raw)

Amr AbdelAziz

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Papers by Amr AbdelAziz

Research paper thumbnail of A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This ... more The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is propose...

Research paper thumbnail of A parallel multi-objective swarm intelligence framework for Big Data analysis

International Journal of Computer Applications in Technology

Research paper thumbnail of A hybrid modified step Whale Optimization Algorithm with Tabu Search for data clustering

Journal of King Saud University - Computer and Information Sciences

Research paper thumbnail of A Pareto-Based Hybrid Whale Optimization Algorithm with Tabu Search for Multi-Objective Optimization

Algorithms

Multi-Objective Problems (MOPs) are common real-life problems that can be found in different fiel... more Multi-Objective Problems (MOPs) are common real-life problems that can be found in different fields, such as bioinformatics and scheduling. Pareto Optimization (PO) is a popular method for solving MOPs, which optimizes all objectives simultaneously. It provides an effective way to evaluate the quality of multi-objective solutions. Swarm Intelligence (SI) methods are population-based methods that generate multiple solutions to the problem, providing SI methods suitable for MOP solutions. SI methods have certain drawbacks when applied to MOPs, such as swarm leader selection and obtaining evenly distributed solutions over solution space. Whale Optimization Algorithm (WOA) is a recent SI method. In this paper, we propose combining WOA with Tabu Search (TS) for MOPs (MOWOATS). MOWOATS uses TS to store non-dominated solutions in elite lists to guide swarm members, which overcomes the swarm leader selection problem. MOWOATS employs crossover in both intensification and diversification phas...

Research paper thumbnail of A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This ... more The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is propose...

Research paper thumbnail of A parallel multi-objective swarm intelligence framework for Big Data analysis

International Journal of Computer Applications in Technology

Research paper thumbnail of A hybrid modified step Whale Optimization Algorithm with Tabu Search for data clustering

Journal of King Saud University - Computer and Information Sciences

Research paper thumbnail of A Pareto-Based Hybrid Whale Optimization Algorithm with Tabu Search for Multi-Objective Optimization

Algorithms

Multi-Objective Problems (MOPs) are common real-life problems that can be found in different fiel... more Multi-Objective Problems (MOPs) are common real-life problems that can be found in different fields, such as bioinformatics and scheduling. Pareto Optimization (PO) is a popular method for solving MOPs, which optimizes all objectives simultaneously. It provides an effective way to evaluate the quality of multi-objective solutions. Swarm Intelligence (SI) methods are population-based methods that generate multiple solutions to the problem, providing SI methods suitable for MOP solutions. SI methods have certain drawbacks when applied to MOPs, such as swarm leader selection and obtaining evenly distributed solutions over solution space. Whale Optimization Algorithm (WOA) is a recent SI method. In this paper, we propose combining WOA with Tabu Search (TS) for MOPs (MOWOATS). MOWOATS uses TS to store non-dominated solutions in elite lists to guide swarm members, which overcomes the swarm leader selection problem. MOWOATS employs crossover in both intensification and diversification phas...

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