dynamic optimization - definitie. Wat is dynamic optimization
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Wat (wie) is dynamic optimization - definitie

PROBLEM OPTIMIZATION METHOD.
Dynamic programming/Implementations and Examples; Dynamic programming more explanation; Dynamic Programming; Dynamic parallelism; Dynamic optimization; List of algorithms that use dynamic programming
  • '''Figure 1.''' Finding the shortest path in a graph using optimal substructure; a straight line indicates a single edge; a wavy line indicates a shortest path between the two vertices it connects (among other paths, not shown, sharing the same two vertices); the bold line is the overall shortest path from start to goal.

Dynamic programming         
Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics.
Dynamic creative optimization         
TERM USED IN PROGRAMMATIC MARKETING
Dynamic Creative Optimization
Dynamic creative optimization (DCO), is a form of programmatic advertising that allows advertisers to optimize the performance of their creative using real-time technology.
Price optimization         
USE OF PRICING METHODS TO MAXIMIZE THE PURCHASING BEHAVIOR OF CONSUMERS
Price optimization software
Price optimization is the use of mathematical analysis by a company to determine how customers will respond to different prices for its products and services through different channels. It is also used to determine the prices that the company determines will best meet its objectives such as maximizing operating profit.

Wikipedia

Dynamic programming

Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics.

In both contexts it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner. While some decision problems cannot be taken apart this way, decisions that span several points in time do often break apart recursively. Likewise, in computer science, if a problem can be solved optimally by breaking it into sub-problems and then recursively finding the optimal solutions to the sub-problems, then it is said to have optimal substructure.

If sub-problems can be nested recursively inside larger problems, so that dynamic programming methods are applicable, then there is a relation between the value of the larger problem and the values of the sub-problems. In the optimization literature this relationship is called the Bellman equation.