Scheduling is inevitable and an integral part of
hospital management. Effective patient scheduling can
improve hospital service quality by minimizing the
waiting/stay time for patients in the hospital and operation
efficiency by optimizing the utilization of resources. However,
in practice, the schedulers usually take substantial amount of
time to do the scheduling manually and also by using various
traditional scheduling algorithms. Motivated by the real needs
in hospital environments this paper focuses on finding an
optimal schedule using search based optimization techniques
like Genetic Algorithm (GA) and multi-Agents. Agents have
been proved to be an effective approach to resource allocation
because of its coordination and social abilities. Exact methods
such as branch and bound method, and dynamic
programming take considerable computing time and
hardware requirements in this application domain.
Considering the crucial time in the hospital environments,
combinatorial search space algorithms (like GA) with
precedence constraints have been selected to find a good
solution with the following objectives: Customer satisfaction
and Operational Efficiency. Customer satisfaction is achieved
by minimizing the waiting time for patients and operational
efficiency by minimizing the idle time of the resource.
%0 Journal Article
%1 egracemarykanaga2010coordinated
%A E.Grace Mary Kanaga, M.L.Valarmathi
%A Rose, J.Dhiviya
%D 2010
%E Das, Dr. Vinu V
%J International Journal on Communication
%K Agents Customer_Satisfaction Operational_Efficiency Patient_Scheduling
%N 3
%P 3
%T Coordinated Multi-Agents Based Patient
Scheduling Using Genetic Algorithm
%U http://doi.searchdl.org/01.IJCOM.1.3.199
%V 1
%X Scheduling is inevitable and an integral part of
hospital management. Effective patient scheduling can
improve hospital service quality by minimizing the
waiting/stay time for patients in the hospital and operation
efficiency by optimizing the utilization of resources. However,
in practice, the schedulers usually take substantial amount of
time to do the scheduling manually and also by using various
traditional scheduling algorithms. Motivated by the real needs
in hospital environments this paper focuses on finding an
optimal schedule using search based optimization techniques
like Genetic Algorithm (GA) and multi-Agents. Agents have
been proved to be an effective approach to resource allocation
because of its coordination and social abilities. Exact methods
such as branch and bound method, and dynamic
programming take considerable computing time and
hardware requirements in this application domain.
Considering the crucial time in the hospital environments,
combinatorial search space algorithms (like GA) with
precedence constraints have been selected to find a good
solution with the following objectives: Customer satisfaction
and Operational Efficiency. Customer satisfaction is achieved
by minimizing the waiting time for patients and operational
efficiency by minimizing the idle time of the resource.
@article{egracemarykanaga2010coordinated,
abstract = {Scheduling is inevitable and an integral part of
hospital management. Effective patient scheduling can
improve hospital service quality by minimizing the
waiting/stay time for patients in the hospital and operation
efficiency by optimizing the utilization of resources. However,
in practice, the schedulers usually take substantial amount of
time to do the scheduling manually and also by using various
traditional scheduling algorithms. Motivated by the real needs
in hospital environments this paper focuses on finding an
optimal schedule using search based optimization techniques
like Genetic Algorithm (GA) and multi-Agents. Agents have
been proved to be an effective approach to resource allocation
because of its coordination and social abilities. Exact methods
such as branch and bound method, and dynamic
programming take considerable computing time and
hardware requirements in this application domain.
Considering the crucial time in the hospital environments,
combinatorial search space algorithms (like GA) with
precedence constraints have been selected to find a good
solution with the following objectives: Customer satisfaction
and Operational Efficiency. Customer satisfaction is achieved
by minimizing the waiting time for patients and operational
efficiency by minimizing the idle time of the resource.},
added-at = {2012-09-27T09:21:47.000+0200},
author = {E.Grace Mary Kanaga, M.L.Valarmathi and Rose, J.Dhiviya},
biburl = {https://www.bibsonomy.org/bibtex/206b991d89e310bcd106200e3873d7bad/ideseditor},
editor = {Das, Dr. Vinu V},
interhash = {9bdcaf05a2706cedaeb8825e31938eb8},
intrahash = {06b991d89e310bcd106200e3873d7bad},
journal = {International Journal on Communication},
keywords = {Agents Customer_Satisfaction Operational_Efficiency Patient_Scheduling},
month = {December},
number = 3,
pages = 3,
timestamp = {2012-09-27T09:21:47.000+0200},
title = {Coordinated Multi-Agents Based Patient
Scheduling Using Genetic Algorithm},
url = {http://doi.searchdl.org/01.IJCOM.1.3.199},
volume = 1,
year = 2010
}