Novel Recursive Technique for Finding the Optimal Solution of the Nurse Scheduling Problem

2019 ◽  
pp. 359-375
Author(s):  
Samah Senbel
Keyword(s):  
Optimal Solution ◽  
Scheduling Problem ◽  
Nurse Scheduling

scholarly journals A hybrid case-based reasoning approach to detecting the optimal solution in nurse scheduling problem

2018 ◽  
Author(s):  
Svetlana Simić ◽  
Dragana Milutinović ◽  
Slobodan Sekulić ◽  
Dragan Simić ◽  
Svetislav D Simić ◽  
...  
Keyword(s):  
Optimal Solution ◽  
Case Based Reasoning ◽  
Scheduling Problem ◽  
Nurse Scheduling ◽  
Case Based

scholarly journals Personnel Scheduling Problem under Hierarchical Management Based on Intelligent Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Li Huang ◽  
Chunming Ye ◽  
Jie Gao ◽  
Po-Chou Shih ◽  
Franley Mngumi ◽  
...  
Keyword(s):  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Grey Wolf Optimizer ◽  
Scheduling Problem ◽  
Nurse Scheduling ◽  
Intelligent Algorithm ◽  
Charge Nurses ◽  
Hierarchical Management ◽  
Two Hybrid ◽  
Better Than

This paper studies a special scheduling problem under hierarchical management in nurse staff. This is a more complex rostering problem than traditional nurse scheduling. The first is that the rostering requirements of charge nurses and general nurses are different under hierarchical management. The second is that nurses are preferable for relative fair rather than absolute fair under hierarchical management. The model aims at allocating the required workload to meet the operational requirements, weekend rostering preferences, and relative fairness preferences. Two hybrid heuristic algorithms based on multiobjective grey wolf optimizer (MOGWO) and three corresponding single heuristic algorithms are employed to solve this problem. The experimental results based on real cases from the Third People’s Hospital, Panzhihua, China, show that MOGWO does not as good as it does on other engineering optimization. However, the hybrid algorithms based on MOGWO are better than corresponding single algorithms on generational distance (GD) and spacing (SP) of Pareto solutions. Furthermore, for relative fair rostering objective, NSGAII-MOGWO has more power to find the optimal solution in the dimension of relative fairness.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

scholarly journals Improving PV Resilience by Dynamic Reconfiguration in Distribution Grids: Problem Complexity and Computation Requirements

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 830
Author(s):  
Filipe F. C. Silva ◽  
Pedro M. S. Carvalho ◽  
Luís A. F. M. Ferreira
Keyword(s):  
Distributed Generation ◽  
Optimal Solution ◽  
Dynamic Reconfiguration ◽  
Scheduling Problem ◽  
Low Carbon ◽  
Distribution Grid ◽  
Medium Voltage ◽  
Classical Computing ◽  
The Impact ◽  
Distribution Grids

The dissemination of low-carbon technologies, such as urban photovoltaic distributed generation, imposes new challenges to the operation of distribution grids. Distributed generation may introduce significant net-load asymmetries between feeders in the course of the day, resulting in higher losses. The dynamic reconfiguration of the grid could mitigate daily losses and be used to minimize or defer the need for network reinforcement. Yet, dynamic reconfiguration has to be carried out in near real-time in order to make use of the most updated load and generation forecast, this way maximizing operational benefits. Given the need to quickly find and update reconfiguration decisions, the computational complexity of the underlying optimal scheduling problem is studied in this paper. The problem is formulated and the impact of sub-optimal solutions is illustrated using a real medium-voltage distribution grid operated under a heavy generation scenario. The complexity of the scheduling problem is discussed to conclude that its optimal solution is infeasible in practical terms if relying upon classical computing. Quantum computing is finally proposed as a way to handle this kind of problem in the future.

A Hybrid Approach to Detecting the Best Solution in Nurse Scheduling Problem

2017 ◽  
pp. 710-721 ◽  
Author(s):  
Svetlana Simić ◽  
Dragan Simić ◽  
Dragana Milutinović ◽  
Jovanka Đorđević ◽  
Svetislav Simić
Keyword(s):  
Hybrid Approach ◽  
Scheduling Problem ◽  
Nurse Scheduling

scholarly journals Realtime production scheduling and control systems in smart industry

Impact ◽  
2020 ◽  
Vol 2020 (8) ◽  
pp. 60-61
Author(s):  
Wei Weng
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Production Scheduling ◽  
Production Control ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Scheduling Problems ◽  
Smart Industry ◽  
And Control

For a production system, 'scheduling' aims to find out which machine/worker processes which job at what time to produce the best result for user-set objectives, such as minimising the total cost. Finding the optimal solution to a large scheduling problem, however, is extremely time consuming due to the high complexity. To reduce this time to one instance, Dr Wei Weng, from the Institute of Liberal Arts and Science, Kanazawa University in Japan, is leading research projects on developing online scheduling and control systems that provide near-optimal solutions in real time, even for large production systems. In her system, a large scheduling problem will be solved as distributed small problems and information of jobs and machines is collected online to provide results instantly. This will bring two big changes: 1. Large scheduling problems, for which it tends to take days to reach the optimal solution, will be solved instantly by reaching near-optimal solutions; 2. Rescheduling, which is still difficult to be made in real time by optimization algorithms, will be completed instantly in case some urgent jobs arrive or some scheduled jobs need to be changed or cancelled during production. The projects have great potential in raising efficiency of scheduling and production control in future smart industry and enabling achieving lower costs, higher productivity and better customer service.

scholarly journals Nonpreemptive Goal Programing Method in Optimization Nurse Scheduling by Considering Education Level

2021 ◽  
Vol 22 (2) ◽  
pp. 85
Author(s):  
Fitriani Utina ◽  
Lailany Yahya ◽  
Nurwan Nurwan
Keyword(s):  
Goal Programming ◽  
Undergraduate Education ◽  
Optimal Solution ◽  
Education Level ◽  
Programming Method ◽  
Nurse Scheduling ◽  
Optimal Service ◽  
Schedule Design ◽  
Good Nurse ◽  
Better Than

Nurse scheduling is one of the problems that often arise in hospital management systems. Head of ICU room and nurse to cooperate in making good nurse scheduling for the creation of optimal service. In this paper, we study a hospital nurse schedule design by considering the level of nurse education and the provision of holidays. Nurses with undergraduate education (S1) Nurses become leaders on every shift and are accompanied by nurses with diploma education (D3). The scheduling model in this study using the nonpreemptive goal programming method and LINGO 11.0 software. The preparation of the schedule of nurses assigned to this method can optimize the need for efficient nurses per shift based on education level. The data in the research was obtained by collecting administrative data at Aloei Saboe Gorontalo hospital. The data used are the published schedule by the head of the ICU room. In making a nurse schedule, there are limitations to consider such ashospital regulation. The results of the study obtained an optimal solution in the form of meeting all the desired obstacles. Computational results shows that nurse scheduling using the nonpreemptive goal programming method and LINGO 11.0 software better than the schedule created manually. Every shift is a maximum of one leader with an undergraduate education (S1) background and accompanied by a nurse with a diploma education (D3) background. Keywords: scheduling, goal programming, nonpreemptive goal programming.

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