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Patterns extracted from good quality solutions can be used to guide the search, leading to a more effective exploration of the solution space.
For the last decades, metaheuristics have become ever more popular as a tool to solve a large class of difficult optimization problems.
However, determining the best configuration of a metaheuristic, which includes the program flow and the parameter settings, remains a difficult task.
Intuition is closely related to heuristics because intuition can be interpreted as layers of experience and knowledge in an area.
The greater your experience of various aspects of the area, and the more niche the area – enabling a concentration of experience – the stronger your intuition can be argued to be.
Experience and loosely applicable information as the basis from which to solve problems immediately sounds potentially flawed.
This is even more of a problem when we recognise that emotions play a substantial role in heuristics and intuition.
So in fact we all use heuristics all the time in making judgements, problem solving and decision making.
The problem with heuristics and intuition could be seen as incomplete information in the face of complex problems.
The errors we make because of the use of heuristics and intuition are called cognitive biases.
We immediately recognise the heuristics of trial & error and rules of thumb, and we have a sense of how they are flawed – arguably because less emotion is used in this type of shortcut.