Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Towards the optical second: verifying optical clocks at the SI limit.

Physical review. X·2024

Same author

rp process and masses of N approximately Z approximately 34 nuclides.

Physical review letters·2009

Same author

Discovery of a nuclear isomer in 65Fe with penning trap mass spectrometry.

Physical review letters·2008

Same author

Experiments with thermalized rare isotope beams from projectile fragmentation: a precision mass measurement of the superallowed beta emitter 38Ca.

Physical review letters·2006

Same author

Post-exercise blood lactate decline after training in competitive cyclists and triathletes.

Research quarterly for exercise and sport·2005

Same author

Motivations and influences on the use of complementary medicine in patients with localized prostate cancer treated with curative intent: results of a pilot study.

BJU international·2003

Search research articles

Related Experiment Video

Updated: Jul 21, 2026

Optimizing the Use of a Liquid Handling Robot to Conduct a High Throughput Forward Chemical Genetics Screen of Arabidopsis thaliana

Optimizing the Use of a Liquid Handling Robot to Conduct a High Throughput Forward Chemical Genetics Screen of Arabidopsis thaliana

Published on: April 30, 2018

Genetic algorithm for scheduling of laboratory personnel.

J C Boyd¹, J Savory

¹Department of Pathology, University of Virginia Health System, PO Box 800214, Charlottesville, VA 22908, USA. jboyd@virginia.edu

Clinical Chemistry

|January 10, 2001

Summary

A genetic algorithm effectively schedules laboratory personnel, ensuring all workstations are covered and staff skills are maintained through rotation. This approach optimizes staffing and identifies training needs in technical work environments.

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Related Experiment Videos

Last Updated: Jul 21, 2026

Optimizing the Use of a Liquid Handling Robot to Conduct a High Throughput Forward Chemical Genetics Screen of Arabidopsis thaliana

Optimizing the Use of a Liquid Handling Robot to Conduct a High Throughput Forward Chemical Genetics Screen of Arabidopsis thaliana

Published on: April 30, 2018

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Area of Science:

Laboratory Management
Operations Research
Computational Biology

Background:

Effective staffing of core laboratories requires systematic scheduling to ensure workstation coverage and skill maintenance.
Periodic exercise of all worker skills is crucial for maintaining staff competence in specialized roles.

Purpose of the Study:

To develop and evaluate a genetic algorithm for optimizing laboratory personnel scheduling.
To ensure appropriate workstation coverage and regular utilization of diverse staff skills.

Main Methods:

A genetic algorithm was developed using Visual Basic 4.0 to schedule laboratory personnel.
The algorithm maximizes a fitness function evaluating the match between personnel, skills, and work tasks for specific shifts.
User inputs include work tasks, personnel availability, skills, shift details, and scheduling parameters via an Excel spreadsheet.

Main Results:

The program successfully matched qualified individuals to tasks and maintained skills through job rotation for over 22 months.
Generated schedules enabled advance anticipation of staffing limitations, facilitating proactive adjustments.
Identified specific skills lacking sufficient trained personnel, aiding targeted training initiatives.
Resulted in an estimated annual saving of approximately $11,000 by reducing supervisory time spent on schedule development.

Conclusions:

Genetic algorithms provide a valuable tool for scheduling in complex, technical work environments with multiskilled employees.
The implemented system demonstrated practical utility and staff acceptance in a large university medical center's clinical laboratories.