Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

79
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
79
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.5K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.5K
Manipulation and Analysis01:21

Manipulation and Analysis

42
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
42
Methods of Documentation II: POMR01:26

Methods of Documentation II: POMR

987
The Problem-Oriented Medical Record (POMR) revolutionized medical record-keeping by introducing a systematic approach focusing on the patient's problems rather than merely listing symptoms. Dr. Lawrence Weed's introduction of this method in the 1960s marked a significant advancement in medical documentation. The POMR framework consists of four key components: the database, problem list, plan of care, and progress notes.
987
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

104
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
104
Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

5.6K
The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
5.6K

You might also read

Related Articles

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

Sort by
Same author

A novel method based on clustering and decision-making for construction project portfolio selection.

PloS one·2026
Same author

The impact of portfolio managers' familiarity with data visualization on the development of heuristics methods.

Cognitive processing·2026
Same author

A Fuzzy Bi-objective Mathematical Model for Perishable Medical Goods Supply Chain Network Considering Crisis Situations: An Empirical Study.

Health services insights·2024
Same author

A Sustainable Multi-Objective Model for Capacitated-Electric-Vehicle-Routing-Problem Considering Hard and Soft Time Windows as Well as Partial Recharging.

Biomimetics (Basel, Switzerland)·2024
Same author

Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches.

Environment, development and sustainability·2022
Same author

A Simulation Optimization Approach for Resource Allocation in an Emergency Department Healthcare Unit.

Global heart·2020

Related Experiment Video

Updated: Jul 17, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

A Multi-objective Mathematical Programing Model for the Problem of P-envy Emergency Medical Service Location.

Mohammad Khalilzadeh1, Arman Bahari2

  • 1CENTRUM Católica Graduate Business School, Pontificia Universidad Católica del Perú, Lima, Peru.

Health Services Insights
|September 4, 2023
PubMed
Summary

This study presents a mathematical model for optimal emergency medical services (EMS) location. The Genetic Algorithm (GA) proved more effective than Simulated Annealing (SA) for maximizing coverage and minimizing costs.

Keywords:
Multi-objective optimization modelP-envyemergency medical servicesfacility locationmedical services costmetaheuristic algorithm

More Related Videos

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.6K
Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.4K

Related Experiment Videos

Last Updated: Jul 17, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.6K
Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.4K

Area of Science:

  • Operations Research
  • Health Systems Management
  • Public Health

Background:

  • Effective emergency medical services (EMS) are crucial for mitigating risks during emergencies.
  • Optimal location of EMS facilities is a significant challenge in healthcare systems worldwide.
  • Balancing patient coverage, construction costs, and service accessibility is essential for healthcare planning.

Purpose of the Study:

  • To develop a multi-objective mathematical programming model for locating and constructing EMS.
  • To maximize patient coverage and survival probability while minimizing EMS construction costs.
  • To optimize the service ratio for regions requiring emergency medical services.

Main Methods:

  • A multi-objective mathematical programming model was formulated.
  • The minimum P-envy algorithm was adapted for EMS location.
  • Genetic Algorithm (GA) and Simulated Annealing (SA) were employed to solve the NP-Hard problem.
  • The Taguchi method was used for tuning metaheuristic algorithm parameters.

Main Results:

  • The proposed model's validity was demonstrated through solving instance problems.
  • The Genetic Algorithm (GA) outperformed the Simulated Annealing (SA) algorithm in solution quality for various problem sizes.
  • GA provided more efficient solutions compared to SA for EMS location and construction.

Conclusions:

  • The developed mathematical model effectively addresses EMS location challenges.
  • GA is a superior metaheuristic algorithm for optimizing EMS placement compared to SA.
  • The findings support improved planning and resource allocation for emergency medical services.