Global optimization and Local search (optimization)

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Global optimization and Local search (optimization)

Global optimization vs. Local search (optimization)

Global optimization is a branch of applied mathematics and numerical analysis that deals with the global optimization of a function or a set of functions according to some criteria. In computer science, local search is a heuristic method for solving computationally hard optimization problems.

Similarities between Global optimization and Local search (optimization)

Global optimization and Local search (optimization) have 8 things in common (in Unionpedia): Feasible region, Iterative method, Mathematical optimization, Metaheuristic, Real number, Simulated annealing, Tabu search, Travelling salesman problem.

Feasible region

In mathematical optimization, a feasible region, feasible set, search space, or solution space is the set of all possible points (sets of values of the choice variables) of an optimization problem that satisfy the problem's constraints, potentially including inequalities, equalities, and integer constraints.

Feasible region and Global optimization · Feasible region and Local search (optimization) · See more »

Iterative method

In computational mathematics, an iterative method is a mathematical procedure that uses an initial guess to generate a sequence of improving approximate solutions for a class of problems, in which the n-th approximation is derived from the previous ones.

Global optimization and Iterative method · Iterative method and Local search (optimization) · See more »

Mathematical optimization

In mathematics, computer science and operations research, mathematical optimization or mathematical programming, alternatively spelled optimisation, is the selection of a best element (with regard to some criterion) from some set of available alternatives.

Global optimization and Mathematical optimization · Local search (optimization) and Mathematical optimization · See more »

Metaheuristic

In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity.

Global optimization and Metaheuristic · Local search (optimization) and Metaheuristic · See more »

Real number

In mathematics, a real number is a value of a continuous quantity that can represent a distance along a line.

Global optimization and Real number · Local search (optimization) and Real number · See more »

Simulated annealing

Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function.

Global optimization and Simulated annealing · Local search (optimization) and Simulated annealing · See more »

Tabu search

Tabu search, created by Fred W. Glover in 1986 and formalized in 1989, is a metaheuristic search method employing local search methods used for mathematical optimization.

Global optimization and Tabu search · Local search (optimization) and Tabu search · See more »

Travelling salesman problem

The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city and returns to the origin city?" It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.

Global optimization and Travelling salesman problem · Local search (optimization) and Travelling salesman problem · See more »

The list above answers the following questions

What Global optimization and Local search (optimization) have in common
What are the similarities between Global optimization and Local search (optimization)

Global optimization and Local search (optimization) Comparison

Global optimization has 67 relations, while Local search (optimization) has 47. As they have in common 8, the Jaccard index is 7.02% = 8 / (67 + 47).

References

This article shows the relationship between Global optimization and Local search (optimization). To access each article from which the information was extracted, please visit:

Unionpedia is a concept map or semantic network organized like an encyclopedia – dictionary. It gives a brief definition of each concept and its relationships.

This is a giant online mental map that serves as a basis for concept diagrams. It's free to use and each article or document can be downloaded. It's a tool, resource or reference for study, research, education, learning or teaching, that can be used by teachers, educators, pupils or students; for the academic world: for school, primary, secondary, high school, middle, technical degree, college, university, undergraduate, master's or doctoral degrees; for papers, reports, projects, ideas, documentation, surveys, summaries, or thesis. Here is the definition, explanation, description, or the meaning of each significant on which you need information, and a list of their associated concepts as a glossary. Available in English, Spanish, Portuguese, Japanese, Chinese, French, German, Italian, Polish, Dutch, Russian, Arabic, Hindi, Swedish, Ukrainian, Hungarian, Catalan, Czech, Hebrew, Danish, Finnish, Indonesian, Norwegian, Romanian, Turkish, Vietnamese, Korean, Thai, Greek, Bulgarian, Croatian, Slovak, Lithuanian, Filipino, Latvian, Estonian and Slovenian. More languages soon.

All the information was extracted from Wikipedia, and it's available under the Creative Commons Attribution-ShareAlike License.

Unionpedia is not endorsed by or affiliated with the Wikimedia Foundation.

Google Play, Android and the Google Play logo are trademarks of Google Inc.