Faster access than browser!Similarities between Computational complexity theory and Optimization problem
Computational complexity theory and Optimization problem have 13 things in common (in Unionpedia): Computational problem, Counting problem (complexity), Decision problem, Feasible region, Function problem, Graph (discrete mathematics), Integer, Knapsack problem, NP (complexity), Operations research, Polynomial-time reduction, Time complexity, Travelling salesman problem.
Computational problem
In theoretical computer science, a computational problem is a mathematical object representing a collection of questions that computers might be able to solve.
Computational complexity theory and Computational problem · Computational problem and Optimization problem ·
Counting problem (complexity)
In computational complexity theory and computability theory, a counting problem is a type of computational problem.
Computational complexity theory and Counting problem (complexity) · Counting problem (complexity) and Optimization problem ·
Decision problem
In computability theory and computational complexity theory, a decision problem is a problem that can be posed as a yes-no question of the input values.
Computational complexity theory and Decision problem · Decision problem and Optimization 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.
Computational complexity theory and Feasible region · Feasible region and Optimization problem ·
Function problem
In computational complexity theory, a function problem is a computational problem where a single output (of a total function) is expected for every input, but the output is more complex than that of a decision problem.
Computational complexity theory and Function problem · Function problem and Optimization problem ·
Graph (discrete mathematics)
In mathematics, and more specifically in graph theory, a graph is a structure amounting to a set of objects in which some pairs of the objects are in some sense "related".
Computational complexity theory and Graph (discrete mathematics) · Graph (discrete mathematics) and Optimization problem ·
Integer
An integer (from the Latin ''integer'' meaning "whole")Integer 's first literal meaning in Latin is "untouched", from in ("not") plus tangere ("to touch").
Computational complexity theory and Integer · Integer and Optimization problem ·
Knapsack problem
The knapsack problem or rucksack problem is a problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible.
Computational complexity theory and Knapsack problem · Knapsack problem and Optimization problem ·
NP (complexity)
In computational complexity theory, NP (for nondeterministic polynomial time) is a complexity class used to describe certain types of decision problems.
Computational complexity theory and NP (complexity) · NP (complexity) and Optimization problem ·
Operations research
Operations research, or operational research in British usage, is a discipline that deals with the application of advanced analytical methods to help make better decisions.
Computational complexity theory and Operations research · Operations research and Optimization problem ·
Polynomial-time reduction
In computational complexity theory, a polynomial-time reduction is a method of solving one problem by means of a hypothetical subroutine for solving a different problem (that is, a reduction), that uses polynomial time excluding the time within the subroutine.
Computational complexity theory and Polynomial-time reduction · Optimization problem and Polynomial-time reduction ·
Time complexity
In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.
Computational complexity theory and Time complexity · Optimization problem and Time complexity ·
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.
Computational complexity theory and Travelling salesman problem · Optimization problem and Travelling salesman problem ·
The list above answers the following questions
- What Computational complexity theory and Optimization problem have in common
- What are the similarities between Computational complexity theory and Optimization problem
Computational complexity theory and Optimization problem Comparison
Computational complexity theory has 164 relations, while Optimization problem has 48. As they have in common 13, the Jaccard index is 6.13% = 13 / (164 + 48).
References
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