Weight Calculator for Graphical Presentation of Nurse Rostering

Authors

  • Vrushali Omkar Salunkhe Bharati Vidyapeeth (Deemed to be University), Institute of Management and Rural Development Administration, Sangli, Maharashtra, India.
  • Pallavi Prasad Jamsandekar Bharati Vidyapeeth (Deemed to be University), Institute of Management and Rural Development Administration, Sangli, Maharashtra, India.

DOI:

https://doi.org/10.70917/ijcisim-2026-3165

Keywords:

Assignment Problem, Bipartite Graph, Graph Theory, Nurse Shift Allocation, HRM

Abstract

The nurse scheduling problem (NSP), also called the nurse rostering problem (NRP), is the operations research problem of finding an optimal way to assign nurses to shifts, typically with a set of hard constraints which all valid solutions must follow, and a set of soft constraints which define the relative quality of valid solutions. The nurse scheduling problem involves the assignment of shifts and holidays to nurses. Each nurse has their own wishes and restrictions, as does the hospital. The problem is described as finding a schedule that satisfies not only the constraints of the nurses available but also the requirements of the hospital. Conventionally, a nurse can work 3 shifts because nursing is shift viz: day shift, night shift, late night shift. After reviewing various literature, researcher observed that, It is tedious task for hospital authority to allocate nurses to appropriate jobs by considering the parameters like duty time (full time or part time), expertise or nurse’s skill, willingness to work in multiple shifts and their mental health. So we try to allocate proper duties to available nurses using big graph and if any other proper solution is there.

Downloads

Download data is not yet available.

Downloads

Published

2026-07-14

How to Cite

Vrushali Omkar Salunkhe, & Pallavi Prasad Jamsandekar. (2026). Weight Calculator for Graphical Presentation of Nurse Rostering. International Journal of Computer Information Systems and Industrial Management Applications, 18(7s), 944–948. https://doi.org/10.70917/ijcisim-2026-3165

Issue

Section

Original Articles