Annealing Harmony Search Algorithm to Solve the Nurse Rostering Problem

作     者：Mohammed Hadwan 

作者机构：Department of Information TechnologyCollege of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer ScienceCollege of Applied SciencesTaiz UniversityTaizYemen Intelligent Analytics Group(IAG)College of ComputerQassim UniversityBuraydahSaudi Arabia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第71卷第6期

页      面：5545-5559页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Qassim University, QU Deanship of Scientific Research, King Saud University 

主　　题：Harmony search algorithm simulated annealing combinatorial optimization problems timetabling metaheuristic algorithms nurse rostering problems 

摘      要：A real-life problem is the rostering of nurses at *** is a famous nondeterministic,polynomial time(NP)-hard combinatorial optimization *** the real-world nurse rostering problem(NRP)constraints in distributing workload equally between available nurses is still a difficult task to *** international shortage of nurses,in addition to the spread of COVID-19,has made it more difficult to provide convenient rosters for *** on the literature,heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity,especially for large ***-based algorithms in general have problems striking the balance between diversification and ***,this paper aims to introduce a novel metaheuristic hybridization that combines the enhanced harmony search algorithm(EHSA)with the simulated annealing(SA)algorithm called the annealing harmony search algorithm(AHSA).The AHSA is used to solve NRP from a Malaysian *** AHSA performance is compared to the EHSA,climbing harmony search algorithm(CHSA),deluge harmony search algorithm(DHSA),and harmony annealing search algorithm(HAS).The results show that the AHSA performs better than the other compared algorithms for all the tested instances where the best ever results reported for the UKMMC dataset.