Global search

As explained in Optimization Algorithms: AI techniques for design, planning, and control problems

A search strategy that explores broadly across the search space to seek a global optimum rather than concentrating only near one current solution.

Global search explores broadly across a search space to locate a global optimum. Unlike local search, which exploits only the neighborhood around the current solution, global search uses more information about the wider space. section 2.2

Global search fits into several useful algorithm classifications:

• Search may be deterministic, following a repeatable procedure, or stochastic, using randomness and potentially producing different paths. section 2.2
• Heuristics seek acceptable solutions in practical time, while metaheuristics guide or modify heuristics to improve their performance. section 2.5
• Global and local search can be considered alongside online versus offline optimization and problem types such as design, planning, and control. section 2.5

Figure 2.16 Deterministic vs. stochastic algorithms. Deterministic algorithms follow a set procedure, and the results are repeatable, while stochastic searches have elements of randomness built into the algorithms.

Use the figure to distinguish repeatable deterministic procedures from stochastic searches that incorporate randomness. section 2.2

How Optimization Algorithms: AI techniques for design, planning, and control problems covers it

How deep it goes

Defines global search through its contrast with local search, but stops short of detailing a particular algorithm’s operations or parameter choices.

What it assumes

Assumes familiarity with search spaces, candidate solutions, current states, and optima while contrasting local and global exploration.

What you can do after

Evaluate/understand whether an optimization method explores globally or concentrates on a current solution’s neighborhood.

How it connects

Ties global search to local search, global optima, deterministic algorithms, stochastic algorithms, heuristics, and metaheuristics.

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Related concepts

• local searchcontrasts with · Local search is an optimization technique that iteratively modifies a candidate solution by exploring neighboring alternatives according to an improvement rule.

This explainer was generated by Manning's knowledge graph from the text of Optimization Algorithms: AI techniques for design, planning, and control problems. The section links point to the parts of the book it draws on.