Operations Research

Definition

Operations research is the discipline of using various and advanced mathematical techniques and methods in order to determine the best solution for a given real-life decision-making problem. It is considered as a branch of the Applied Mathematics field, and sometimes considered the same as decision-making science and management science. Operations research focuses on practical and real-world applications, applying multiple mathematical methods to obtain optimal (when using exact methods) or near-optimal (when using approximative methods). [1]

Who

There is no one-size-fits-all path for how to become an operations research analyst. However, there are some steps individuals interested in entering this exciting field can follow.

Whether seeking an entry-level position or looking ahead to a graduate program, those interested in becoming an operations research analyst should begin with a bachelor’s degree. Popular undergraduate programs that can lead to a career as an operations research analyst include data science, math, or business.

Becoming an operations research analyst requires significant skills in quantitative analysis, so courses in advanced mathematics are critical. Coursework should include calculus, statistics, and linear algebra. Students should also have some understanding of computer science and technology. The work an operations research analyst does may draw from many different sciences, including psychology, economics, political science, and engineering. Coursework in these disciplines can help prepare for graduate studies or professional work in operations research. [4]

What

Operations Research can be defined as the study of mathematical models and analytical methods used to make better decisions in complex situations. It involves the use of quantitative techniques to analyze data and provide insights that can be used to improve business processes and performance.

Operations Research is often used to solve optimization problems, such as minimizing costs or maximizing profits. Still, it can also be applied to other areas, such as risk analysis, project management, and supply chain management. [2]

Operations Research Techniques

Linear Programming (LP): Linear programming is a mathematical technique used to optimize a linear objective function subject to linear constraints. LP is widely used in operations research to solve optimization problems.
Integer Programming (IP): Integer programming is a variant of LP where the decision variables are restricted to integer values. This technique is often used in problems where the decision variables represent discrete quantities.
Dynamic Programming (DP): Dynamic programming is a technique used to solve problems that can be broken down into smaller subproblems and solved recursively. DP is often used in problems that involve sequential decision-making.
Decision Analysis: Decision analysis is used to make decisions under uncertainty by assigning probabilities to various outcomes. This technique is often used in problems where the decision-maker must choose between several options with uncertain outcomes.
Queuing Theory: Queuing theory is used to study and analyze waiting lines or queues. This technique is often used in problems where the goal is to minimize waiting times or maximize throughput.
Simulation: Simulation involves creating a model of a real-world system and using it to study its behaviour. This technique is often used in problems where it is difficult or expensive to perform real-world experiments.
Network Analysis: A technique used to analyze complex networks and their properties. This technique is often used in problems where the goal is to optimize the flow of resources through a network.

Why

Operations research (OR) is a discipline that deals with the application of mathematical, statistical, and analytical techniques to help make better decisions. OR problems typically involve the allocation and control of limited resources, and they can arise in a wide variety of settings, including business, government, and the military.

OR practitioners use a variety of tools and techniques to solve problems, including:

Mathematical modeling: This involves developing mathematical models of the problem that can be used to simulate different scenarios and evaluate the impact of different decisions.
Statistical analysis: This involves collecting and analyzing data to identify trends and patterns that can be used to make better decisions.
Data mining: This involves using statistical techniques to extract hidden patterns and trends from large datasets.
Computer simulation: This involves using computers to create virtual models of real-world systems that can be used to test different hypotheses and solutions.

OR has been used to solve a wide variety of problems, including:

Optimizing production schedules: OR can be used to help companies determine the best way to schedule production in order to minimize costs and maximize output.
Routing delivery vehicles: OR can be used to help companies determine the best way to route delivery vehicles in order to minimize travel time and fuel costs.
Allocating resources: OR can be used to help companies allocate resources, such as personnel and equipment, in order to maximize efficiency and minimize costs.
Managing risk: OR can be used to help companies manage risk, such as the risk of stock market fluctuations or natural disasters.

OR is a powerful tool that can be used to improve decision-making in a wide variety of settings. By applying OR techniques, companies can save money, improve efficiency, and increase profits. [3]

See Theoretical Knowledge Vs Practical Application.

How

Many of the References and Additional Reading websites and Videos will assist you with understating and applying operations research.

As some professors say: “It is intuitively obvious to even the most casual observer.“

References

[1] ms-academy. 2022. “Operations Research: The Science Of Doing Better.” Math Academy. July 28. https://www.mathacademytutoring.com/blog/operations-research-the-science-of-doing-better.

[2] Singh, Vikram. “What Is Operations Research?” 2024. Shiksha. Accessed June 9. https://www.shiksha.com/online-courses/articles/operations-research-blogId-157427.

[3] Maiti, Sushanta. 2023. “Operations Research: Evolution, Process, Characteristics, and Pros & Cons.” EDUCATIONLEAVES. June 13. https://educationleaves.com/operations-research/.

[4] “How to Become an Operations Research Analyst.” 2023. Maryville University Online. October 11. https://online.maryville.edu/online-masters-degrees/data-science/careers/how-to-become-operations-research-analyst/.

Additional Reading

“Heuristics on the High Seas: Mathematical Optimization for Cargo Ships.” 2024. Google Research. Accessed June 9. https://research.google/blog/heuristics-on-the-high-seas-mathematical-optimization-for-cargo-ships/.

Look around you. Chances are that something in your line of sight sailed on a cargo ship. 90% of the world’s goods travel over the ocean, often on cargo vessels mammoth in scale: a quarter mile long, weighing 250,000 tons, holding 12,000 containers of goods collectively worth a billion dollars. Unlike airplanes, trains, and trucks, cargo ships are in nearly constant operation, following cyclical routes across oceans.

But, what are the best, most efficient routes for these ships? To a computer scientist, this is a graph theory problem; to a business analyst, a supply chain problem. Done poorly, containers linger at ports, ships idle offshore unable to berth, and ultimately, products become pricier as the flow of physical items becomes slower and unpredictable. Every container shipping company needs to solve these challenges, but they are typically solved separately. Combining them multiplies the complexity, and, to the best of our knowledge, is a problem that has never been solved at the scale required by the largest container operations (500 vessels and 1500 ports).

Videos

What is Operation Research?

Operations research (OR) is a field of applied mathematics, engineering, and management science that deals with the application of advanced analytical methods to help make better decisions. OR uses quantitative models and data analysis to address complex issues in a variety of fields, including business, government, and healthcare.

[Part 1] Introduction to Operations Research – History, OR Today, Models, Structure, & Phases of OR

This is the Part 1 the tutorial video series on the Introduction of Operations Research. Here, we will talk about the History and the Development of OR, the structure of mathematical modelling, the different phases to conduct an OR study, and the different types of models.

⭐ I suggest that you read the entire reference. Other references can be read in their entirety but I leave that up to you.

The featured image on this page is from the shiksha online website.