) for a sample list of inequations Similar to
equation solving,
inequation solving means finding what values (numbers, functions, sets, etc.) fulfill a condition stated in the form of an inequation or a conjunction of several inequations. These expressions contain one or more
unknowns, which are free variables for which values are sought that cause the condition to be fulfilled. To be precise, what is sought are often not necessarily actual values, but, more in general, expressions. A
solution of the inequation is an assignment of expressions to the
unknowns that satisfies the inequation(s); in other words, expressions such that, when they are substituted for the unknowns, make the inequations true propositions. Often, an additional
objective expression (i.e., an optimization equation) is given, that is to be minimized or maximized by an
optimal solution. For example, :0 \leq x_1 \leq 690 - 1.5 \cdot x_2 \;\land\; 0 \leq x_2 \leq 530 - x_1 \;\land\; x_1 \leq 640 - 0.75 \cdot x_2 is a conjunction of inequations, partly written as chains (where \land can be read as "and"); the set of its solutions is shown in blue in the picture (the red, green, and orange line corresponding to the 1st, 2nd, and 3rd conjunct, respectively). For a larger example. see Linear programming#Example. Computer support in solving inequations is described in
constraint programming; in particular, the
simplex algorithm finds optimal solutions of linear inequations. The programming language
Prolog III also supports solving algorithms for particular classes of inequalities (and other relations) as a basic language feature. For more, see
constraint logic programming. == Combinations of meanings ==