scholarly journals A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 38
Author(s):  
Amr Mohamed AbdelAziz ◽  
Louai Alarabi ◽  
Saleh Basalamah ◽  
Abdeltawab Hendawi
Keyword(s):  
Medical Care ◽  
Real Life ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Admission Process ◽  
Multi Objective ◽  
Admission Time ◽  
King Faisal Specialist Hospital ◽  
Number Of Patients ◽  
Massive Number

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 proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals Mechanical properties optimization of the steering column based on multi-objective optimization design

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668294 ◽  
Author(s):  
Si Chen ◽  
Zhaohui Wang ◽  
Mi Lv
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Optimization Design ◽  
Strain Difference ◽  
Optimization Method ◽  
Equivalent Strain ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Multi Objective ◽  
Initial Results

The mechanical properties of the steering column have a significant influence on the comfort and stability of a vehicle. In order for the mechanical properties to be improved, the rotary swaging process of the steering column is studied in this article. The process parameters, including axial feed rate, hammerhead speed, and hammerhead radial reduction, are systematically analyzed and optimized based on a multi-objective optimization design. The response surface methodology and the genetic algorithm are employed for optimal process parameters to be obtained. The maximum damage value, the maximum forming load, and the equivalent strain difference obtained with the optimal process parameters are, respectively, decreased by 30.09%, 7.44%, and 57.29% compared to the initial results. The comparative results present that the quality of the steering column is improved. The torque experiments and fatigue experiments are conducted with the optimal steering column. The maximum torque is measured to be 260 NM, and the service life is measured to be 2 weeks (40 NM, 2500 times), which are, respectively, increased by 8.3% and 8.69% compared to the initial results. The above results display that the mechanical properties of the steering column are optimized to verify the feasibility of the multi-objective optimization method.

Multi-Objective Topology Optimization for Bevel Gear and Geometrical Reconstruction

2013 ◽  
Vol 278-280 ◽  
pp. 139-142
Author(s):  
Xiang Bian ◽  
Zong De Fang ◽  
Kun Qin ◽  
Lifei Lian ◽  
Bao Yu Zhang
Keyword(s):  
Topology Optimization ◽  
Optimization Method ◽  
Tooth Root ◽  
Multi Objective Optimization ◽  
Direct Optimization ◽  
Multi Objective ◽  
Gear Modification ◽  
Parametric Cad ◽  
Straight Lines ◽  
Root Stress

Usually the gear modification is a main measure to reduce the vibration and noise of the gears, but in view of the complexity of the gear modification, topology optimization method was used to optimize the structure of the gear. The minimum volume was set as the direct optimization goal. To achieve the target of reducing contact stress, tooth root bending stress and improving flexibility, the upper bound of the stress and lower bound of the flexibility were set appropriately, thus realizing multi-objective optimization indirectly. A method for converting topology result into parametric CAD model which can be modified was presented, by fitting the topology result with simple straight lines and arcs, the model can be smoothed automatically, after further regulating, the geometry reconstruction was finished. After topology optimization, the resulting structure and properties of the gear are consistent with cavity gear. While reducing the weight of the gear, the noise can be reduced and its life would be extended through increasing flexibility and reducing tooth root stress.

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