Examples of global search

• Then more than a dozen software packages for complete global search are described.

• It is therefore evident that a global search of the entire solution space has a tendency to be computationally intractable.

• This same example is estimated to require over 20,000 years to solve by a global search on a similar machine.

• The basic idea of global search is to represent and manipulate sets of candidate solutions or solution spaces.

• In the rest of the paper we illustrate the process of deriving a global search algorithm by applying it to an example.

• The efficiency of global search methods enables us to keep only small solution fragments, which leads to a larger neighbourhood leaving more room for improvement.

• The population-based genetic algorithm can be regarded as a global search algorithm whereas representative-agent-type search algorithms are necessarily local.

• The procedure has shown to be competitive compared to both the pure global search procedure and simple local search methods based on simpler neighbourhoods.

• Each node in the global search tree consists of a solution to a conjunctive problem plus the set of remaining disjunctions.

• In particular, we explore the distinction between global search and local search.

• The key idea is that at each step, a given neighbourhood of a certain solution is searched using a global search approach.

• This global search approach is used for completing fragments into solutions in the local search approach (same branching scheme).

• Global search is used to find the best solution within a neighbourhood.

• The algorithm consistently displays drastic improvements over a global search with demonstrated effort reduction of up to six orders of magnitude.

• They are effective at performing global search (in probability) instead of local optima.