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Pseudocode. In computer science, pseudocode is a description of the steps in an algorithm using a mix of conventions of programming languages (like assignment operator, conditional operator, loop) with informal, usually self-explanatory, notation of actions and conditions. [1][2] Although pseudocode shares features with regular programming ...
Local search (optimization) In computer science, local search is a heuristic method for solving computationally hard optimization problems. Local search can be used on problems that can be formulated as finding a solution that maximizes a criterion among a number of candidate solutions. Local search algorithms move from solution to solution in ...
Tabu search (TS) is a metaheuristic search method employing local search methods used for mathematical optimization. It was created by Fred W. Glover in 1986 [1] and formalized in 1989. [2][3] Local (neighborhood) searches take a potential solution to a problem and check its immediate neighbors (that is, solutions that are similar except for ...
Travelling Salesman, by director Timothy Lanzone, is the story of four mathematicians hired by the U.S. government to solve the most elusive problem in computer-science history: P vs. NP. [77] Solutions to the problem are used by mathematician Robert A. Bosch in a subgenre called TSP art.
Luhn algorithm. The Luhn algorithm or Luhn formula, also known as the " modulus 10" or "mod 10" algorithm, named after its creator, IBM scientist Hans Peter Luhn, is a simple check digit formula used to validate a variety of identification numbers. It is described in US patent 2950048A, granted on 23 August 1960. [1]
The approximation of a normal distribution with a Monte Carlo method. Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle.
Greedy algorithms fail to produce the optimal solution for many other problems and may even produce the unique worst possible solution. One example is the travelling salesman problem mentioned above: for each number of cities, there is an assignment of distances between the cities for which the nearest-neighbour heuristic produces the unique ...
Definition. LP-type problems were defined by Sharir & Welzl (1992) as problems in which one is given as input a finite set S of elements, and a function f that maps subsets of S to values from a totally ordered set. The function is required to satisfy two key properties: Monotonicity: for every two sets A ⊆ B ⊆ S, f (A) ≤ f (B) ≤ f (S).