Operational Research

TL;DR

• Uses quantitative methods to design and evaluate systems that improve efficiency, reduce costs, and boost organizational performance.
• Applies mathematical models and statistical analysis across sectors such as manufacturing, transportation, finance, and healthcare.
• Often combines tools like linear programming, simulation, and decision analysis and requires integration of mathematics, statistics, computer science, and engineering.

Definition

Operational research (OR) is a discipline that focuses on the application of scientific methods, mathematical models, and statistical analysis to solve complex problems in various fields, such as business, engineering, and healthcare. OR aims to improve the efficiency, effectiveness, and performance of organizations and systems through the use of scientific approaches and tools.

Explanation

Operational research applies quantitative and analytical techniques to real-world operational problems. It uses mathematical models, statistical analysis, and computer-based methods to analyze data and design solutions that optimize systems and decision-making. OR techniques are frequently combined with methods such as linear programming, simulation, and decision analysis. The field integrates knowledge from multiple disciplines—mathematics, statistics, computer science, and engineering—to design and implement effective solutions.

OR has a historical origin dating back to World War II, when it was used to solve military problems related to logistics, transportation, and communication. Since then, the discipline has evolved and expanded into business, engineering, healthcare, and other sectors, contributing to improved organizational performance and system optimization.

Examples

Supply chain optimization

Supply chain management involves the planning, coordination, and control of activities involved in the production, distribution, and delivery of goods and services. In order to optimize the supply chain, OR techniques are often used to analyze data and design systems that minimize costs, reduce waste, and improve customer satisfaction. For instance, OR methods can be used to optimize the routing and scheduling of vehicles in a transportation network, to determine the optimal inventory levels for a warehouse, or to design efficient logistics systems for the distribution of goods.

Healthcare resource allocation

In the healthcare industry, OR techniques can be used to optimize the allocation of resources, such as beds, staff, and equipment, in order to improve the quality of care and reduce costs. For example, OR methods can be used to determine the optimal number of beds needed in a hospital, based on the expected demand for services and the available resources. OR can also be used to develop mathematical models that predict the likelihood of patients requiring certain types of care, such as surgery or rehabilitation, and to allocate resources accordingly. In addition, OR can be used to design efficient systems for the delivery of healthcare services, such as hospital networks or ambulatory care centers.

Use cases

Operational research has a wide range of applications and can be used to solve problems in various sectors, including:

• Manufacturing
• Transportation
• Finance
• Healthcare

OR provides evidence-based solutions that help organizations improve efficiency, reduce costs, and increase competitiveness, and it supports data-driven decision making.

Notes or pitfalls

• OR techniques are often used in combination with other tools and methods, such as linear programming, simulation, and decision analysis.
• Effective OR requires integrating multiple disciplines—mathematics, statistics, computer science, and engineering—to design and implement solutions.

Related terms

• Linear programming
• Simulation
• Decision analysis
• Mathematics
• Statistics
• Computer science
• Engineering