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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 first condition of solving a problem is understanding the problem, which can be done by way of a problem statement. [1]
Problem discovery is an unconscious process which depends upon knowledge whereby an idea enters one's conscious awareness, problem formulation is the discovery of a goal; problem construction involves modifying a known problem or goal to another one; problem identification represents a problem that exists in reality but needs to be discovered ...
The problem formulation stated above is a convention called the negative null form, since all constraint function are expressed as equalities and negative inequalities with zero on the right-hand side. This convention is used so that numerical algorithms developed to solve design optimization problems can assume a standard expression of the ...
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.
The answer to a research question will help address a research problem or question. [5] Specifying a research question, "the central issue to be resolved by a formal dissertation, thesis, or research project," [6] is typically one of the first steps an investigator takes when undertaking research.
The assignment problem is a fundamental combinatorial optimization problem. In its most general form, the problem is as follows: The problem instance has a number of agents and a number of tasks. Any agent can be assigned to perform any task, incurring some cost that may vary depending on the agent-task assignment.
To ensure that the global maximum of a non-linear problem can be identified easily, the problem formulation often requires that the functions be convex and have compact lower level sets. This is the significance of the Karush–Kuhn–Tucker conditions. They provide necessary conditions for identifying local optima of non-linear programming ...
For each combinatorial optimization problem, there is a corresponding decision problem that asks whether there is a feasible solution for some particular measure m 0. For example, if there is a graph G which contains vertices u and v , an optimization problem might be "find a path from u to v that uses the fewest edges".