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Mathematical optimization, also known as mathematical programming, are specific techniques that include algorithms applied to optimize or solve problems related to difference fields of the human existence, including scientific research, medical science, economics and engineering.
In general, the concept of optimization involves the search for best possible solutions through analysis and investigation. The goal of optimization can be to increase gain, profitability, precision and effectiveness or to decrease loss and risk.
In healthcare, sophisticated computational techniques, decision analysis and optimization can help solve problems related to demographics, socio-economic variables, resources, patient complaints, risk factors for common diseases and treatment outcomes.
Experts in mathematical programming look at decision variables and try to either minimize of maximize their function. Equations and complicated mathematical formulas are how optimization happens in practice when solving real life, scientific or mathematical problems.
One of the first examples of mathematical optimization can be tracked back to the 1930s, which was applied by the US Air force team in order to improve allocation of scarce resources in the post-war economic crisis. Hence, mathematical coordination and planning was used to improve the use of military resources. Since then, a variety of optimization techniques have been used in terms of:
Experts in mathematical programming usually have PhD in a mathematical-related field and are able to work on different topics:
- Facilitate testing of hypothesis
- Mathematical models applied to web development
- Scientific problem solving, used in relation to:
One of the principles of mathematical optimization is that quantitative problems in different fields share several mathematical elements, therefore these professionals use similar methods and principles. In some areas, optimization has led to major advances, such as computer science, numerical analysis, economics, research and combinatorics.
Despite similarities in the way complex are solved in different areas, each specific question requires a unique mathematical model to be developed.
This complex field requires skilled professionals with highly analytical minds. Mathematicians and data scientists who work on a freelance basis charge from 50 USD per hour. Depending on the project, a total fixed fee can be negotiated with the freelancer.
There are a few consultancy agencies offering mathematical optimization, however, working with freelancers considerably decreases the total cost for a project. Also, you can hire help on an ad-hoc basis as challenges arise.
- Project description or scope of work: be clear on your needs, on the details for your project, on the decision variables and constrain factors. If you have an idea on what is required, you can mention if you will need linear or non-linear programming.
- Duration of the project: how long should it take for the freelancer to complete your project?
- By when you need to hire: are you in a hurry to hire or would you rather take time to find someone with experience in your specific field?
- Budget: decide between a fee per hour or a fixed rate for the entire project.
- Skills required: what kind of experience do you want to find in the freelancer?
Mathematical optimization ultimately facilitates decision-making in different setting, from science to economics, from biological data to distribution of resources. If you need help with this kind of solution, you can hire a freelance expert in applied mathematics and optimization with ease and establish a good collaboration that will benefit your work.
Ready to hire an expert in mathematical optimization? Post your project on Kolabtree and get quotes from experts for free.