scholarly journals An Optimization Algorithms-based Approach to District Health System Population Areas in Iran

2020 ◽  
Author(s):  
Javad Tayyebi ◽  
Sobhan Mostafayi Darmian
Keyword(s):  
Differential Evolution ◽  
Health System ◽  
Healthcare System ◽  
Operations Management ◽  
Particle Swarm ◽  
Healthcare Management ◽  
System Structure ◽  
Particle Swarm Algorithm ◽  
District Health ◽  
Strategic Model

Background: One of important subject in the operations' management fields is partitioning matter that was investigated in the study. This topic has recently received more attention from researchers of the healthcare management systems' field. This subject is important because planning about improvement of the healthcare system structure is considered as one of the most important management problems in each society. The goal of solving this problem was to district a society into several areas, so that each area can cover its  health services completely. Methods: This fundamental-applied study was conducted based on the Genetic optimization algorithm, particle swarm, and differential evolution to improve the current structures with regard to the existing health structure in Iran. Moreover, the health system strategic model was applied to categorize the population regions into 10 partitions. According to nature of the investigated problem, the objective function is maximizing the equilibrium amount in each district. The constraints included exclusive assignment and not-existing unusual assignment. Unusual assignment is defined as existence of no contiguity and holes in partitions. Results: According to the obtained results, the particle swarm algorithm had the most efficiency, while differential evolution had the lowest efficiency. However, the stated constraints were satisfied completely in all algorithms, which represented appropriate efficiency of the modified algorithm in the generation solutions. Conclusion: The results obtained from solving this problem can be used as a useful tool in improving the existing healthcare system in Iran.

Chronicity of disruptive project rhythms: The projectification of the ‘post-Ebola' health system rebuilding in Sierra Leone

2021 ◽  
pp. 0961463X2110052
Author(s):  
Michaela Hubmann
Keyword(s):  
Public Health ◽  
Global Health ◽  
Health System ◽  
Sierra Leone ◽  
Linear Time ◽  
Healthcare Management ◽  
Public Healthcare ◽  
District Health ◽  
Time Frames ◽  
Health Programmes

Global health development projects are inherently governed by bounded, temporal and linear time frames: the initiation, implementation and ending of time-limited interventions. This projectification of global health programmes has wide-reaching consequences as global health projects, often unsustainable and produces both new life possibilities and uncertain futures. This article highlights the temporal effects of the global health agenda on the primary health system rebuilding efforts in Sierra Leone. Attention is paid to how the projectification of public health programmes affected the primary healthcare management in a district in the southern region of Sierra Leone. Throughout this article, I develop the theoretical concept of chronicity of disruptive project rhythms where local public healthcare actors encounter project disruptions on a continuum of chronic lack. I base this concept on Manderson and Smith-Morris’s definition of chronicity of illness experience, which is marked by punctuated episodes of acute sickness, where chronic patients are temporally transmuted into acute patients, while at the same time continuing to suffer from their ongoing chronic ailments. Drawing on 14 months of ethnographic research, I show how a district health management team (DHMT) contested the bounded time frames of public health funding; how waiting time for funding impacted the operation of the DHMT and, by extension, the district health system as a whole and how DHMT employees and other actors within the health system employed time-tricking strategies to resist this project time.

scholarly journals Performance Comparison between Particle Swarm Optimization and Differential Evolution Algorithms for Postman Delivery Routing Problem

2021 ◽  
Vol 11 (6) ◽  
pp. 2703
Author(s):  
Warisa Wisittipanich ◽  
Khamphe Phoungthong ◽  
Chanin Srisuwannapa ◽  
Adirek Baisukhan ◽  
Nuttachat Wisittipanit
Keyword(s):  
Particle Swarm Optimization ◽  
Differential Evolution ◽  
Particle Swarm ◽  
Performance Comparison ◽  
Swarm Optimization ◽  
Routing Problem ◽  
Metaheuristic Methods ◽  
Evolution Algorithms ◽  
Differential Evolution Algorithms ◽  
Current Practices

Generally, transportation costs account for approximately half of the total operation expenses of a logistics firm. Therefore, any effort to optimize the planning of vehicle routing would be substantially beneficial to the company. This study focuses on a postman delivery routing problem of the Chiang Rai post office, located in the Chiang Rai province of Thailand. In this study, two metaheuristic methods—particle swarm optimization (PSO) and differential evolution (DE)—were applied with particular solution representation to find delivery routings with minimum travel distances. The performances of PSO and DE were compared along with those from current practices. The results showed that PSO and DE clearly outperformed the actual routing of the current practices in all the operational days examined. Moreover, DE performances were notably superior to those of PSO.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

Sign in / Sign up

Export Citation Format

Share Document