A heuristic algorithm based on multi-assignment procedures for nurse scheduling

被引:25
|
作者
Constantino, Ademir Aparecido [1 ]
Landa-Silva, Dario [2 ]
de Melo, Everton Luiz [1 ]
Xavier de Mendonca, Candido Ferreira [3 ]
Rizzato, Douglas Baroni [1 ]
Romao, Wesley [1 ]
机构
[1] Univ Estadual Maringa, Dept Comp Sci, BR-87020900 Maringa, Parana, Brazil
[2] Univ Nottingham, Sch Comp Sci, Nottingham NG8 1BB, England
[3] State Univ Sao Paulo, Sch Arts Sci & Humanities, BR-03828000 Sao Paulo, Brazil
基金
英国工程与自然科学研究理事会;
关键词
Nurse scheduling problem; Assignment problem; Heuristic algorithms; Combinatorial optimization; SEARCH;
D O I
10.1007/s10479-013-1357-9
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses' preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust.
引用
收藏
页码:165 / 183
页数:19
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