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Nurse scheduling problem

Nurse scheduling problem is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Nurse scheduling problem rather than just read about it. In short: 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. Solutions to the nurse scheduling problem can be applied to constrained scheduling…

Key takeaways

  • Nurse scheduling problem belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Nurse scheduling problem to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Nurse scheduling problem from memory before moving on to harder problems.

Reference excerpt

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. Solutions to the nurse scheduling problem can be applied to constrained scheduling problems in other fields. While research on computer-assisted employee scheduling goes back to the 1950s, the nurse scheduling problem in its current form was introduced in two parallel publications in 1976. It is known to have NP-hard complexity.

General description Conventionally, hospital nursing is shift work that is divided up to provide coverage 24 hours per day, 7 days per week. The hospital has restrictions and requirements for what coverage is needed, and each nurse has their own wishes and restrictions as well. The problem is described as finding a schedule that fulfills the objectives of the hospital and covers all shifts, while respecting as many of the nurses' preferences as possible. The problem is not unique to nursing. It applies in any other profession or situation where shift coverage must be planned out.

Constraints Creating a schedule means attempting to satisfy certain constraints on how that schedule is laid out. There are two types of constraint: hard constraints, which must be met for the schedule to be valid; and soft constraints, which are desirable but not mandatory. Depending on the policies of a hospital, the preferences of individual nurses may be treated as either a soft constraint, or as a hard constraint.

Hard constraints may include physical limitations or legal requirements. Some examples of possible hard constraints are:

All shifts require nursing coverage. A nurse cannot work more than one shift at the same time. A nurse cannot work more than 24 hours in a day, or more than 7 days in a week. A nurse must not work more than a legally specified number of days in a row. A nurse must have a legally specified number of rest hours between shifts. Any newly licensed nurse must be paired with an experienced nurse. There must always be one charge nurse on duty. Certain shifts must be covered by nurses with special qualifications.

Soft constraints may be hospital policies or nurse preferences. Some examples of possible soft constraints are:

All nurses should work approximately the same number of weekend shifts. All nurses should work approximately the same difficulty in shift assignments. A nurse should not work a day shift and a night shift without a rest day in between. One nurse prefers to have all their work days in a row, and then have all their days off in a row. One nurse prefers to work no more than two consecutive days, with a day off in between. One nurse cannot work Wednesday each week because they have no child care available that day. Two nurses feel they work well together and prefer to be scheduled to work together.

Solutions Solutions to the problem use a variety of techniques, including both mathematically exact solutions and a variety of heuristic solutions using decomposition, parallel computing, stochastic optimization, genetic algorithms, colony optimization, simulated annealing, quantum annealing, Tabu search, and coordinate descent. Burke et al. (2004) summarised the state of art of academic research to the nurse rostering problem, including brief introductions of various then published solutions.

See also Assignment problem Constraint programming Employee scheduling software

References

Worked examples

Example 1 — a first encounter with Nurse scheduling problem

Start with the simplest possible case. Write down what Nurse scheduling problem claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Nurse scheduling problem before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Nurse scheduling problem ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Nurse scheduling problem

In research
Nurse scheduling problem appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Nurse scheduling problem in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Nurse scheduling problem is common in secondary-school and first-year university syllabi. It links to neighbouring topics Constraint programming, Nursing informatics, Optimal scheduling, so understanding it makes those chapters shorter.
In everyday life
Look for Nurse scheduling problem outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Nurse scheduling problem in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Nurse scheduling problem means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Nurse scheduling problem out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Nurse scheduling problem in simple terms?

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…

Why does Nurse scheduling problem matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Nurse scheduling problem?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Nurse scheduling problem.

Tags

  • Constraint programming
  • Nursing informatics
  • Optimal scheduling
  • Time management

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