A heuristic approach to improving the design of nurse training schedules
1995
European Journal of Operational Research
1
81
50-61
Journal_Article
Personnel_Planning_and_Scheduling||Wards||Equitable_Resource_Allocation
Algorithms_Heuristics||Simulation_Monte_carlo_methods||Decision_support_systems
Tactical
No
Yes
Article Link
Nooriafshar, M. (1995). A heuristic approach to improving the design of nurse training schedules. [Journal Article]. European Journal of Operational Research, 81(1), 50-61. doi: 10.1016/0377-2217(93)e0131-g
Thetransitional period simulation program (TRANSIM) along with its supporting data base programs constitute a package which has been developed as part of the author's Ph.D. research. The software has been written in such a way that it can readily, with minimal modification, be transferred to any computer which supports BASIC. The system can simulate staffing levels of trainee nurses on wards, and identify overstaffings and understaffings. The results are produced in graphical format which will make it easy for the user to evaluate. Although the package has been designed specially for simulating staffing levels during the transition period, it can also be used to predict the combined effect of a number of existing concurrent courses of different types on the staffing levels of the hospital wards. An extended version of the simulation program incorporates the ideas of expert systems; and the software algorithm uses experiential or judgemental knowledge of the allocation officers to produce possible plans of action for re-scheduling the training courses in such a way that minimal overstaffings and understaffings on wards are achieved. An approach similar to that of Ernst and Newell's Mean Ends analysis of GPS was adopted, and a constraint directed reasoning approach was used to reduce the difference between the initial and the goal states, to achieve satisfactory solutions. The experience gained from developing TRANSIM has led to further work and research in the general area of scheduling and resource allocation.