Mathematical optimization or mathematic programming is a scientific discipline which allows us, within any economic, productive or engineering context, answering questions such as
How much room for improvement do we have?
How can we reach that improvement?
To answer these questions, any economic, productive or engineering problem might be transformed into a mathematical model. Mathematical programming helps us finding the optimal solution among millions of possible alternatives
ESCISSION has developed algorithms that have extended the capabilities of the products there are at present for solving mathematical programming problems in highly uncertain environments.
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Optimization is a branch of mathematics that enables any physical or symbolic system to be planned, operated and modified once its internal rules and final objectives have been defined. Stochastic optimization goes one step further by taking the variability of the input variables and rules into account, in order to answer the following questions:
What is the most appropriate configuration of a system for reaching any given goal when faced with uncertainty?
What are the most appropriate operating rules in a system in which results are maximized, and a set of restrictions on use and risks of failure are fulfilled?
What is the most robust way of expanding a given system under conditions of uncertainty in future operating scenarios?
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Most of the technical and financial decisions industry faces at present can be framed within a stochastic optimization problem: how to maximize or minimize results with some restrictions, taking into account the uncertainty associated with the input variables and operating rules.
Structural and Hydraulic
Structural design, dam design, highway design, water resources and reservoir management, etc.
Renewable energy generation, energy transportation, power hiring, etc.
Economy & finances
Stock trades, logistics, investment strategies and portfolios optimization, etc.