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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 ...
In pseudocode, this algorithm would look as follows. The algorithm does not use complex numbers and manually simulates complex-number operations using two real numbers, for those who do not have a complex data type. The program may be simplified if the programming language includes complex-data-type operations.
Dinic's algorithm: is a strongly polynomial algorithm for computing the maximum flow in a flow network. Edmonds–Karp algorithm: implementation of Ford–Fulkerson. Ford–Fulkerson algorithm: computes the maximum flow in a graph. Karger's algorithm: a Monte Carlo method to compute the minimum cut of a connected graph.
Literate Programming by Donald Knuth is the seminal book on literate programming.. Literate programming is a programming paradigm introduced in 1984 by Donald Knuth in which a computer program is given as an explanation of how it works in a natural language, such as English, interspersed (embedded) with snippets of macros and traditional source code, from which compilable source code can be ...
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 ...
PSeInt is the abbreviation of PSe udocode In terpreter, an educational tool created in Argentina, used mainly by students to learn the basics of programming and the development of logic. It is a very popular software of its kind and is widely used in universities in Latin America and Spain. It uses pseudocode for the solution of algorithms.
Backtracking. Backtracking is a class of algorithms for finding solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons a candidate ("backtracks") as soon as it determines that the candidate cannot possibly be completed to a valid solution. [1]
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 ...