The Nurse Rostering Problem

Parallel Genetic Algorithmic approaches for Nurse Rostering

Ms. Swapnaja S. Balekar

ME student, Dept. of CE,

Smt. Kashibai Navale College of Engg,

Vadgaon, MS, India. [e-mail] Ms. N. A. Mhetre

Assistant Professor, Dept. of CE,

Smt. Kashibai Navale College of Engg,

Vadgaon, MS, India. [e-mail] Abstract--Nurse Rostering is a complex problem which arises in everyday activities and health care system in modern hospitals. The Nurse Rostering Problem[NRP] is a subclass of the personnel scheduling problems, and most of its instances are NP-hard. Even though solving the Nurse Rostering Problem has been interested field for research from many years, still the Nurse Rostering is done manually. This paper provides the

The Nurse Rostering Problem (NRP) is a common problem every hospital has to deal with every day. Nurse roster is a working plan for all available nurses, obtained by matching nurses to shift categories. NRP belongs to the class of personnel scheduling problems and aims to provide an optimal schedule based on the working hours of the nurses, their personal preferences, hospital regulations and law of hospitality. A very general form of the nurse rostering problem could be described as follows: Given a set of shifts and a set of nurses over a certain time period, assign each shift to a nurse subject to a set of constraints. Mainly, constraints are stated by regulations, working practices and the preferences of the nurses. Most of its variants are NP-hard, and represent an interesting field of research and development. Osogami and Imai[70] (2000) proved that the nurse rostering problem is NP-hard. In fact, they proved that the timetabling problem, which is NP-complete, can be transformed into a decision version of the nurse rostering problem with only a subset of the real world constraints that apply to

Minimum time between shifts on successive working days Avoid too many consecutive working days.

Maximum weekly working time must be considered.

2) Problem type

Depending on constraints, a NRP generally can be classified as Optimization Problem or a Decision problem[1].

Optimization problem: The problem was formulated to minimize or maximize an objective function. Mathematical Programming is an exact approach to combinatorial Optimization Programming. Traditional methods from linear programming, integer programming, GP networks have been employed to solve the NRP.

Decision Problem: In situations where there are a large number of constraints to be dealt with, it can be more appropriate to model the NRP as a constraint satisfaction Problem (CSP). Feasible solutions to the CSP are the assignments of values to variables satisfying all constraints. Decision problems usually solve by Heuristics or