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Related Experiment Video

Updated: Oct 13, 2025

Field Experiments of Pollination Ecology: The Case of Lycoris sanguinea var. sanguinea

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Published on: November 25, 2016

Discrete flower pollination algorithm for patient admission scheduling problem.

Zahraa A Abdalkareem¹, Mohammed Azmi Al-Betar², Amiza Amir³

¹Faculty of Electronic Engineering Technology, University Malaysia Perlis, 02600 Arau, Perlis, Malaysia; Alimam Aladham University College, Baghdad, Iraq.

Computers in Biology and Medicine

|November 17, 2021

Summary

This study introduces a discrete flower pollination algorithm (DFPA) to solve the complex patient admission scheduling problem (PASP) in healthcare. The DFPA efficiently optimizes patient assignments to hospital resources, enhancing patient comfort and streamlining healthcare operations.

Keywords:

Combinatorial optimization Discretization Flower pollination algorithm Meta-heuristics Patient admission scheduling problem

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Area of Science:

Health Informatics
Operations Research
Computational Intelligence

Background:

The Patient Admission Scheduling Problem (PASP) is a critical challenge in healthcare management.
PASP involves complex combinatorial optimization for assigning patients to hospital resources under strict constraints.
Maximizing patient comfort is a key objective in effective healthcare scheduling.

Purpose of the Study:

To introduce a novel meta-heuristic optimization method for the PASP.
To adapt the Flower Pollination Algorithm (FPA) for discrete optimization domains relevant to healthcare scheduling.
To enhance the algorithm's search capabilities through various neighborhood structures.

Main Methods:

Application of the Discrete Flower Pollination Algorithm (DFPA) to the PASP.
Discretization of the continuous FPA for suitability in combinatorial problems.
Utilizing diverse neighborhood structures to improve solution exploration.

Main Results:

The DFPA demonstrated high efficiency in solving the PASP.
Performance was evaluated on benchmark datasets against existing algorithms.
The method proved effective in optimizing patient scheduling and resource allocation.

Conclusions:

The Discrete Flower Pollination Algorithm is a highly efficient method for the PASP.
This approach offers a promising solution for improving healthcare scheduling and patient comfort.
The DFPA's adaptability suggests potential for broader applications in complex scheduling problems.