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Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields.
Brute-force search. In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solving technique and algorithmic paradigm that consists of systematically checking all possible candidates for whether or not each candidate satisfies the problem's statement.
Creative problem-solving ( CPS) [1] is the mental process of searching for an original and previously unknown solution to a problem. To qualify, the solution must be novel and reached independently.
Computational thinking means thinking or solving problems like computer scientists. CT refers to thought processes required in understanding problems and formulating solutions. CT involves logic, assessment, patterns, automation, and generalization.
A problem statement is a description of an issue to be addressed or a condition to be improved upon. It identifies the gap between the current problem and goal. The problem statement should be designed to address the Five Ws. The first condition of solving a problem is understanding the problem, which can be done by way of a problem statement.
Trial and error is a fundamental method of problem-solving [1] characterized by repeated, varied attempts which are continued until success, [2] or until the ...
An American-style crossword grid layout. A crossword (or crossword puzzle) is a word game consisting of a grid of black and white squares, into which solvers enter words or phrases ("entries") crossing each other horizontally ("across") and vertically ("down") according to a set of clues. Each white square is typically filled with one letter ...
Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. [1] [2] It is generally divided into two subfields: discrete optimization and continuous optimization.