A Global Optimum is the best possible solution among all feasible options. It’s the highest peak or lowest valley in an entire landscape, as opposed to a local optimum which is the best solution within a specific region.
- Best overall solution: It’s the ultimate goal in optimization problems.
- Difficult to find: Identifying the global optimum can be challenging, especially in complex problems.
- Often requires advanced techniques: Specialized algorithms and methods are often needed to find global optima.
Example:
Continuing the mountain analogy, the global optimum would be the highest peak in the entire mountain range, not just the highest point in a particular valley.
While local optima are good starting points, the ultimate goal is to find the global optimum, which represents the best possible outcome.