What's the first step in planning an operations research project?

Operations research (OR) is a discipline that uses mathematical models and analytical methods to help decision-makers optimize complex systems and processes. OR can be applied to various fields, such as engineering, business, logistics, healthcare, and military. However, before you can start solving any OR problem, you need to plan your project carefully. What's the first step in planning an OR project?

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1 Define the problem

The first step in planning an OR project is to define the problem clearly and precisely. You need to understand the objectives, constraints, assumptions, and criteria of the problem, as well as the relevant data and information. You also need to identify the stakeholders, their roles, and their expectations. A well-defined problem will guide you to select the appropriate OR methods and tools, and to communicate your results effectively.

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2 Review the literature

The second step in planning an OR project is to review the existing literature on the problem and the related topics. You need to find out what previous studies have done, what gaps and limitations they have, and what insights and recommendations they offer. You also need to learn the theoretical foundations, the mathematical formulations, and the computational techniques of the OR methods and tools that you plan to use. A thorough literature review will help you to avoid reinventing the wheel, to benchmark your solution, and to justify your approach.

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3 Design the model

The third step in planning an OR project is to design the model that represents the problem and its essential features. You need to choose the type of model, such as linear, nonlinear, integer, stochastic, or dynamic, that suits your problem and your data. You also need to define the variables, parameters, functions, and constraints that describe the relationships and interactions among the elements of the problem. A good model will capture the complexity and uncertainty of the problem, while being simple and realistic enough to solve.

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Steven Stark

Top Operations Research Voice on LinkedIn | Follow for OR, Python, Interviewing Content and More | All Opinions are my own
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"A good model will capture the complexity and uncertainty of the problem, while being simple and realistic enough to solve." Just make sure that you don't make the problem too simple that it doesn't actually model the problem at hand.

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4 Select the solution method

The fourth step in planning an OR project is to select the solution method that can find the optimal or near-optimal solution for your model. You need to consider the characteristics of your model, such as its size, structure, linearity, convexity, and integrality, and the availability of your data, such as its quality, quantity, and format. You also need to evaluate the advantages and disadvantages of different solution methods, such as exact, heuristic, metaheuristic, or simulation-based methods, and their computational requirements and performance. A suitable solution method will balance the trade-off between accuracy and efficiency.

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Steven Stark

Top Operations Research Voice on LinkedIn | Follow for OR, Python, Interviewing Content and More | All Opinions are my own
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This section has good ideas, but it's possible you may not need to go through a heavy evaluation period of various techniques. For instance, let's say I need to be able to solve the problem within an hour. It turns out that I can find the provable optimal solution using CPLEX within a few seconds. Do I really need to explore a meta-heuristic at this point? My time would probably be better spent elsewhere.

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5 Plan the analysis and presentation

The fifth step in planning an OR project is to plan the analysis and presentation of your solution and its implications. You need to determine how to validate, test, and compare your solution, and how to measure its quality, robustness, and sensitivity. You also need to decide how to visualize, summarize, and interpret your solution, and how to communicate it to your stakeholders and audience. A comprehensive analysis and presentation will demonstrate the value and impact of your solution, and support your recommendations and conclusions.

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6 Manage the project

The sixth step in planning an OR project is to manage the project throughout its life cycle. You need to define the scope, schedule, budget, and resources of your project, and monitor and control them regularly. You also need to coordinate and collaborate with your team members, stakeholders, and clients, and manage the expectations, risks, and changes of your project. A well-managed project will ensure the quality, timeliness, and feasibility of your solution, and the satisfaction of your stakeholders and clients.

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Steven Stark

Top Operations Research Voice on LinkedIn | Follow for OR, Python, Interviewing Content and More | All Opinions are my own
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This step should actually be the first step. Once the problem has been defined by leadership, not formulated mathematically though, that's when planning to manage the project should begin. You don't want people to spend too much time formulating the problem or doing literature reviews. You'll want people to be on track to meet deadlines from the very beginning of the project.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What's the first step in planning an operations research project?

1

2

3

4

5

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1 Define the problem

2 Review the literature

3 Design the model

4 Select the solution method

5 Plan the analysis and presentation

6 Manage the project

7 Here’s what else to consider

Operations Research

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What's the first step in planning an operations research project?

1

2

3

4

5

6

7

1 Define the problem

2 Review the literature

3 Design the model

4 Select the solution method

5 Plan the analysis and presentation

6 Manage the project

7 Here’s what else to consider

Operations Research

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