Synthesis of Employer and Employee Satisfaction–Case Nurse Rostering in a Finnish Hospital

Workforce management has become increasingly important for both the public sector and private companies. Workforce optimization encompasses all aspects of managing the complete workforce lifecycle. The goal is to optimize the performance of staff on both financial efficiency and customer satisfaction. This paper presents a successful process to optimize employer and employee satisfaction simultaneously. The slightly improved PEAST algorithm is used to roster nurses in a Finnish Hospital. The results show that it is possible to successfully optimize employer and employee satisfaction simultaneously. The generated schedules are highly acceptable for the hospital’s administration. The algorithm has been integrated into the market-leading workforce management software in Finland. The paper also introduces three simple test problems which will help researchers to test the value of their optimization methods. 

[1]  Kimmo Nurmi,et al.  Days-off scheduling for a bus transportation company , 2011 .

[2]  Andreas T. Ernst,et al.  Staff scheduling and rostering: A review of applications, methods and models , 2004, Eur. J. Oper. Res..

[3]  Nasser R. Sabar,et al.  A harmony search algorithm for nurse rostering problems , 2013, Inf. Sci..

[4]  Patrick De Causmaecker,et al.  Polynomially solvable formulations for a class of nurse rostering problems , 2014 .

[5]  Dries R. Goossens,et al.  Scheduling a triple round robin tournament with minitournaments for the Finnish national youth ice hockey league , 2014, J. Oper. Res. Soc..

[6]  Michael J. Brusco,et al.  A sequential integer programming method for discontinuous labor tour scheduling , 1996 .

[7]  Patrick De Causmaecker,et al.  A categorisation of nurse rostering problems , 2011, J. Sched..

[8]  Marko Elovainio,et al.  Extending Employment beyond the Pensionable Age: A Cohort Study of the Influence of Chronic Diseases, Health Risk Factors, and Working Conditions , 2014, PloS one.

[9]  Dario Landa Silva,et al.  A heuristic algorithm based on multi-assignment procedures for nurse scheduling , 2013, Ann. Oper. Res..

[10]  Kimmo Nurmi,et al.  Solving the person-based multitask shift generation problem with breaks , 2013, 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO).

[11]  Kimmo Nurmi,et al.  THE CORE STAFF ROSTERING PROBLEM , 2016, IMECS 2016.

[12]  Gerhard F. Post,et al.  Driver rostering for bus transit companies , 2011 .

[13]  K. Nurmi,et al.  Using the PEAST Algorithm to Roster Nurses in an Intensive-Care Unit in a Finnish Hospital , 2012 .

[14]  Dries Goossens,et al.  Scheduling a professional sports league using the PEAST algorithm , 2014, IMECS 2014.

[15]  Avishai Mandelbaum,et al.  Telephone Call Centers: Tutorial, Review, and Research Prospects , 2003, Manuf. Serv. Oper. Manag..

[16]  Dániel Marx,et al.  RAPH COLORING PROBLEMS AND THEIR APPLICATIONS IN SCHEDULING , 2022 .

[17]  Sanja Petrovic,et al.  METAHEURISTICS FOR HANDLING TIME INTERVAL COVERAGE CONSTRAINTS IN NURSE SCHEDULING , 2006, Appl. Artif. Intell..

[18]  Ya-Tzu Chiang,et al.  CYBER SWARM ALGORITHMS FOR MULTI-OBJECTIVE NURSE ROSTERING PROBLEM , 2013 .

[19]  Kimmo Nurmi,et al.  Crucial Components of the PEAST Algorithm in Solving Real-World Scheduling Problems , 2013 .

[20]  Hoong Chuin Lau,et al.  On the complexity of manpower shift scheduling , 1996, Comput. Oper. Res..

[21]  Fred Glover.  New Ejection Chain and Alternating Path Methods for Traveling Salesman Problems , 1992, Computer Science and Operations Research.

[22]  Patrick De Causmaecker,et al.  Local search neighbourhoods to deal with a novel nurse rostering model , 2008 .

[23]  George B. Dantzig,et al.  Letter to the Editor - A Comment on Edie's "Traffic Delays at Toll Booths" , 1954, Oper. Res..

[24]  Patrick De Causmaecker,et al.  Local search neighbourhoods for dealing with a novel nurse rostering model , 2012, Ann. Oper. Res..

[25]  Nicolas Chapados,et al.  Retail Store Workforce Scheduling by Expected Operating Income Maximization , 2011, CPAIOR.

[26]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[27]  Guy Kortsarz,et al.  The minimum shift design problem , 2007, Ann. Oper. Res..

[28]  Sanja Petrovic,et al.  A hybrid metaheuristic case-based reasoning system for nurse rostering , 2009, J. Sched..

[29]  K. Nurmi,et al.  Optimizing Large-Scale Staff Rostering Instances , 2012 .

[30]  Amnon Meisels,et al.  Modelling and Solving Employee Timetabling Problems , 2003, Annals of Mathematics and Artificial Intelligence.

[31]  Steven Walczak,et al.  Nurse Scheduling: From Academia to Implementation or Not? , 2007, Interfaces.

[32]  Nysret Musliu,et al.  XHSTT: an XML archive for high school timetabling problems in different countries , 2014, Ann. Oper. Res..

[33]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[34]  Celso C. Ribeiro,et al.  A Framework for Scheduling Professional Sports Leagues , 2010 .

[35]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[36]  Kimmo Nurmi,et al.  Workforce Scheduling Using the PEAST Algorithm , 2014 .

[37]  James M. Tien,et al.  On Manpower Scheduling Algorithms , 1982 .

[38]  Zheng-Yun Zhuang,et al.  Optimized Workforce Scheduling in Bus Transit Companies , 2013, 2013 Fourth Global Congress on Intelligent Systems.

[39]  Nysret Musliu,et al.  Scheduling Breaks in Shift Plans for Call Centers , 2008 .

[40]  Hesham K. Alfares,et al.  Survey, Categorization, and Comparison of Recent Tour Scheduling Literature , 2004, Ann. Oper. Res..