Related Experiment Videos
Multiobjective prioritization methodology and decision support system for evaluating inventory enhancement strategies
Joanna Resurreccion1, Joost R Santos
1The GeorgeWashington University, Washington, DC, USA.
Summary
Disaster preparedness is improved by enhancing inventory in critical manufacturing sectors. This reduces recovery time and economic losses, boosting regional infrastructure resilience.
Area of Science:
- Operations Research
- Disaster Management
- Economic Modeling
Background:
- Disasters disrupt infrastructure and economic sectors, causing cascading inoperability and amplified losses due to interdependencies.
- Existing dynamic inoperability input-output models (DIIM) need enhanced methods for prioritizing sectors for disaster preparedness.
Purpose of the Study:
- To evaluate inventory-enhanced policies for disrupted interdependent sectors using DIIM.
- To develop a dynamic prioritization methodology for improving disaster preparedness capabilities.
Main Methods:
- Development of the dynamic cross-prioritization plot (DCPP) to identify and update critical sectors based on objectives.
- Integration of risk assessment metrics (economic loss, inoperability) within the DIIM framework.
- Creation of a computer-based DCPP tool incorporating user preferences and resource availability for inventory enhancement prioritization.
Main Results:
- A baseline analysis in Virginia identified manufacturing sectors as critical for inoperability and service sectors for economic loss.
- Simulations of enhanced inventory policies for critical manufacturing sectors reduced recovery time by approximately four days.
- Enhanced inventory policies also decreased expected total economic loss by $33 million.
Conclusions:
- The DCPP is an effective decision support tool for prioritizing inventory enhancement to bolster regional disaster resilience.
- Further analysis is recommended for managing the resilience of service sectors.
- The DCPP methodology offers flexibility for application in diverse regions and disaster scenarios.
Related Concept Videos
01:28Methods of Medium Optimization
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
01:09Decision Making: P-value Method
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 have a...
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 have a...
01:14Decision Making: Traditional Method
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
01:30Health Information Technology and Healthcare Information System
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
01:20Integrated Healthcare System
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
01:16Response Surface Methodology
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps: