Simulated Annealing Algorithm for Daily Nursing Care Scheduling Problem

Abstract

Nursing, with the primary mission to provide quality services to patients, is accompanied by a serial of activities like patients assessment, outcomes identification for patients. In general, there has been less attention on ensuring that nurses provide nursing cares in a timely and accurate fashion. Consequently, in this paper, considering the similarity to the traditional job shop scheduling problems, we will model the daily nursing care scheduling problems and propose an efficient scheduling method based on simulated annealing algorithm. By the comparison of several nursing care plans obtained by the dispatching-rule based methods (which have been recognized to be the implementation of human thoughts), the proposed method is evaluated to be applicable to the nursing care scheduling problems (providing comprehensive, coordinated and cost effective nursing cares to patients).

Applicability of artificial bee colony algorithm for nurse scheduling problems

“…In the literature study by Ref. 23 16. The need of a nurse for any shift (minimum, maximum or specified number) In this study, the grouping specified in the study of Cheang et al 23 has been taken consideration based on 1, 5, 6, 7, 10, 12, 13, 15, 16 constraint types.…”

“…Dias et al 12 , Chiaramonte and Chiaramonte 14 , Maenhout and Vanhoucke 15 improved new heuristic models for nurse scheduling problem. Cheng et al 16 , Parr and Thompson 17 , used simulated annealing method for nurse scheduling. Maenhout and Vanhoucke 18 and Brucker et al 19 , set new data sets to compare suggested different models.…”

Cloud Based Hybrid Evolution Algorithm for NP-Complete Pattern in Nurse Scheduling Problem

“…Some researches proposed to find the optimal solution based on mathematical programming method, linear programming, nonlinear programming, multi-objective programming, dynamic programming, parameter planning, heuristic algorithm, hill-climbing algorithm, simulated annealing algorithm, etc. [13]- [18].…”

A heuristic algorithm for nurse scheduling with balanced preference satisfaction

“…Many of these methods use meta-heuristic approaches, like the Electromagnetic method [10], Scatter Search [9], various Genetic Algorithms [11], [12], [13], [14], Tabu Search [15], Variable Neighbourhood Search (VNS) [16], GRASP [17], Memetic Algorithms [18], and Simulated Annealing [19].…”