A Differential Evolution Algorithm Developed for a Nurse Scheduling Problem

Abstract

Nurse scheduling is a type of manpower allocation problem that tries to satisfy hospital managers' objectives and nurses' preferences as much as possible by generating fair shift schedules. This paper presents a nurse scheduling problem based on a real case study, and proposes two meta-heuristics -a differential evolution algorithm (DE) and a greedy randomised adaptive search procedure (GRASP) -to solve it. To investigate the efficiency of the proposed algorithms, two problems are solved. Furthermore, some comparison metrics are applied to examine the reliability of the proposed algorithms. The computational results in this paper show that the proposed DE outperforms the GRASP. OPSOMMINGVerpleegsterskedulering is 'n mannekragtoedelingsprobleem wat deur regverdige skofskedules beide hospitaalbestuurders se teikens en verpleegpersoneel se voorkeure bevredig. Dié artikel handel oor 'n verpleegsterskeduleringprobleem wat gebaseer is op 'n werklike gevallestudie en stel twee metaheuristieke voor om die probleem op te los -'n differensiaal evolusionêre metode en 'n gulsige, ewekansige, aanpasbare soekprosedure. Om die doeltreffendheid van die voorgestelde algoritmes te ondersoek word twee probleme opgelos. Verder word vergelykende maatstawwe gebruik om die betroubaarheid van die voorgestelde algoritmes te ondersoek. Die berekende resultate in die artikel toon dat die differensiaal evolusionêre algoritme beter vaar as die gulsige, ewekansige, aanpasbare soekprosedure.

Interactive Nurse Scheduling

“…Many of them have been thoroughly described by Burke et al, 27 who divided the solutions into several categories based on their practical applicability, performance measures, constraints, and methodological approach (eg, operations research techniques or artificial intelligence methods). Bard and Purnomo 29 proposed an integer program for solving the NSP that also considered the quality of individual schedules in terms of avoidance of specific and undesirable shifts; Beddoe et al 30 proposed a hybrid metaheuristic case-based reasoning system for solving the NSP in large medical centers, and Shahnazari-Shahrezaei et al 31 introduced a dual metaheuristic approach based on the differential evolution algorithm and a greedy randomized adaptive search procedure for solving the NSP in an Iranian hospital's maternity ward. More recently, van den Bergh et al 32 provided a bibliographic presentation of the state-of-the-art and categorized methods based on personnel characteristics, decision delineations, shift definitions, constraints, performance measures, and flexibility.…”

Personnel Scheduling Problem under Hierarchical Management Based on Intelligent Algorithm

“…In equation (25), "in any week" of S1 indicates any seven consecutive days in the roster and so does equation (26). In equation ( 26), "night shifts" of S2 6 Complexity include shifts E and N and so do equations ( 30) and ( 34)-(36). is is because in the studied hospital, the ratio of nurses to beds in the ward is lower than the criterion of the Ministry of Health (0.4:1), and nurses frequently feel tired after work, especially after shift E or shift N. Classifying Shift E and shift N into "night shifts" is to reduce nurses' fatigue in rostering.…”

“…e other is fairness preferences, which is to pursue absolute fairness in the same level and accept relative fairness among different levels. Literature research on fair rostering mainly focuses on the following aspects: (1) fair workload allocation [5], (2) fair shifts assignment [6][7][8], (3) fair distribution of contractual violations [9], and (4) fair allocation of special time, such as vacations [10], weekends, and nights [11]. e research on fair rostering has acquired rich achievements but mainly focused on the absolute fairness for all nurses.…”

The Improved Differential Evolution Algorithm for Multi-Floor Facility Layout Problems

“…Xu and Wen (2012 ) employed DE to the unidirectional logistics distribution vehicle routing problem with no time widows resulting in the shortage total distance. Scheduling problem, Shahnazari-Shahrezaei et al (2012) present DE to generate the fair shift Nurse Scheduling problem base on a real case study. Zhang et al (2013) adapted DE method dealing with the job shop problem in order to minimize total tardiness.…”