Full Text:   <2061>

CLC number: TP391; O226

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2018-03-15

Cited: 0

Clicked: 5962

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Chun-hua He

http://orcid.org/0000-0002-6517-7208

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.3 P.446-458

http://doi.org/10.1631/FITEE.1601802


Tabu search based resource allocation in radiological examination process execution


Author(s):  Chun-hua He

Affiliation(s):  College of Medical Engineering Technology, Xinjiang Medical University, Urumqi 830011, China

Corresponding email(s):   460938212@qq.com

Key Words:  Radiological examination process (REP), Resource scheduling and allocation, Tabu search


Chun-hua He. Tabu search based resource allocation in radiological examination process execution[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(3): 446-458.

@article{title="Tabu search based resource allocation in radiological examination process execution",
author="Chun-hua He",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="19",
number="3",
pages="446-458",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601802"
}

%0 Journal Article
%T Tabu search based resource allocation in radiological examination process execution
%A Chun-hua He
%J Frontiers of Information Technology & Electronic Engineering
%V 19
%N 3
%P 446-458
%@ 2095-9184
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601802

TY - JOUR
T1 - Tabu search based resource allocation in radiological examination process execution
A1 - Chun-hua He
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 19
IS - 3
SP - 446
EP - 458
%@ 2095-9184
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1601802


Abstract: 
Efficient resource scheduling and allocation in radiological examination process (REP) execution is a key requirement to improve patient throughput and radiological resource utilization and to manage unexpected events that occur when resource scheduling and allocation decisions change due to clinical needs. In this paper, a tabu search based approach is presented to solve the resource scheduling and allocation problems in REP execution. The primary objective of the approach is to minimize a weighted sum of average examination flow time, average idle time of the resources, and delays. Unexpected events, i.e., emergent or absent examinations, are also considered. For certain parameter combinations, the optimal solution of radiological resource scheduling and allocation is found, while considering the limitations such as routing and resource constraints. Simulations in the application case are performed. Results show that the proposed approach makes efficient use of radiological resource capacity and improves the patient throughput in REP execution.

放射检查流程执行中基于禁忌搜索的资源分配

概要:放射检查流程(radiological examination process,REP)执行中,为提高患者吞吐量和放射资源利用率,以及应对因临床需要而改变资源调度和分配决策时发生的突发事件,高效的资源调度和分配是关键。本文提出一种基于禁忌搜索的方法,用以解决REP执行中资源调度和分配问题。该方法主要目标是将平均检查流时间、资源平均空闲时间和延迟的加权总和最小化,同时还考虑突发事件的情形,即紧急或缺失的检查。对于特定参数组合,在考虑路由和资源约束等限制条件下,该方法能找到放射资源调度和分配的最优解。对应用案例进行了仿真,结果表明该方法能有效利用放射资源,提高REP执行中患者吞吐量。

关键词:放射检查流程(REP);资源调度和分配;禁忌搜索

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Aickelin U, Dowsland KA, 2004. An indirect genetic algorithm for a nurse-scheduling problem. Comput Oper Res, 31(5):761-778.

[2]Bard JF, Purnomo HW, 2005. Hospital-wide reactive scheduling of nurses with preference considerations. IIE Trans, 37(7):589-608.

[3]Beck JC, Fox MS, 2000. Constraint-directed techniques for scheduling alternative activities. Artif Intell, 121(1-2):211-250.

[4]Błażewicz J, Pesch E, Sterna M, 2000. The disjunctive graph machine representation of the job shop scheduling problem. Eur J Oper Res, 127(2):317-331.

[5]Brah SA, Loo LL, 1999. Heuristics for scheduling in a flow shop with multiple processors. Eur J Oper Res, 113(1):113-122.

[6]Cheang B, Li H, Lim A, et al., 2003. Nurse rostering problems—a bibliographic survey. Eur J Oper Res, 151(3):447-460.

[7]Duftschmid G, Miksch S, Gall W, 2002. Verification of temporal scheduling constraints in clinical practice guidelines. Artif Intell Med, 25(2):93-121.

[8]Elmaghraby SE, 1993. Resource allocation via dynamic programming in activity networks. Eur J Oper Res, 64(2):199-215.

[9]Glover F, 1986. Future paths for integer programming and links to artificial intelligence. Comput Oper Res, 13(5):533-549.

[10]Huang ZX, van der Aalst WMP, Lu LD, et al., 2010. An adaptive work distribution mechanism based on reinforcement learning. Exp Syst Appl, 37(12):7533-7541.

[11]Huang ZX, Lu XD, Duan HL, 2011a. Mining association rules to support resource allocation in business process management. Exp Syst Appl, 38(8):9483-9490.

[12]Huang ZX, van der Aalst WMP, Lu XD, et al., 2011b. Reinforcement learning based resource allocation in business process management. Data Knowl Eng, 70(1):127-145.

[13]Kim SC, Horowitz I, Young KK, et al., 2000. Flexible bed allocation and performance in the intensive care unit. J Oper Manag, 18(4):427-443.

[14]Kubzin MA, Potts CN, Strusevich VA, 2009. Approximation results for flow shop scheduling problems with machine availability constraints. Comput Oper Res, 36(2):379-390.

[15]Marinagi CC, Spyropoulos CD, Papatheodorou C, et al., 2000. Continual planning and scheduling for managing patient tests in hospital laboratories. Artif Intell Med, 20(2):139-154.

[16]Mika M, Waligóa G, Węglarz J, 2008. Tabu search for multi-mode resource-constrained project scheduling with schedule-dependent setup times. Eur J Oper Res, 187(3):1238-1250.

[17]Negenman EG, 2001. Local search algorithms for the multiprocessor flow shop scheduling problem. Eur J Oper Res, 128(1):147-158.

[18]Oddi A, Cesta A, 2000. Toward interactive scheduling systems for managing medical resources. Artif Intell Med, 20(2):113-138.

[19]Roland B, di Martinelly C, Riane F, et al., 2010. Scheduling an operating theatre under human resource constraints. Comput Ind Eng, 58(2):212-220.

[20]Salimifard K, Wright M, 2001. Petri net-based modelling of workflow systems:an overview. Eur J Oper Res, 134(3):664-676.

[21]Spyropoulos CD, 2000. AI planning and scheduling in the medical hospital environment. Artif Intell Med, 20(2):101-111.

[22]Verhoeven MGA, 1998. Tabu search for resource-constrained scheduling. Eur J Oper Res, 106(2-3):266-276.

[23]Vermeulen IB, Bohte SM, Elkhuizen SG, et al., 2009. Adaptive resource allocation for efficient patient scheduling. Artif Intell Med, 46(1):67-80.

[24]Vilcot G, Billaut JC, 2008. A tabu search and a genetic algorithm for solving a bicriteria general job shop scheduling problem. Eur J Oper Res, 190(2):398-411.

[25]Zhang JY, Lu XD, Nie HC, et al., 2009. Radiology information system:a workflow-based approach. Int J Comput Assist Radiol Surg, 4(5):509-516.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE