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Context	English	Santali
Options.xhp par_id0603200910394248 help.text	Specifies the probability for an individual to choose the Differential Evolution strategy.
Options.xhp par_id0603200910394277 help.text	DE: Crossover Probability
Options.xhp par_id0603200910394280 help.text	… defines the probability of the individual being combined with the globally best point. If crossover is not used, the point is assembled from the own memory of the individual.
Options.xhp par_id0603200910394216 help.text	DE: Scaling Factor
Options.xhp par_id060320091039424 help.text	During crossover, the scaling factor decides about the “speed” of movement.
Options.xhp par_id060320091039421 help.text	PS: Constriction Coefficient
Options.xhp par_id0603200910394225 help.text	… defines the speed at which the particles/individuals move towards each other.
Options.xhp par_id0603200910394222 help.text	PS: Cognitive Constant
Options.xhp par_id0603200910394212 help.text	… sets the importance of the own memory (in particular the best reached point so far).
Options.xhp par_id0603200910394292 help.text	PS: Social Constant
Options.xhp par_id0603200910394284 help.text	… sets the importance of the global best point between all particles/individuals.
Options.xhp par_id060320091039425 help.text	PS: Mutation Probability
Options.xhp par_id0603200910394272 help.text	… defines the probability, that instead of moving a component of the particle towards the best point, it randomly chooses a new value from the valid range for that variable.
Options.xhp hd_id0603200910401383 help.text	SCO-specific Options
Options.xhp par_id0603200910401382 help.text	Size of Library
Options.xhp par_id060320091040136 help.text	… defines the amount of information to store in the public library. Each individual stores knowledge there and asks for information.	… defines the amount of information to store in the public library. Each individual stores knowledge there and asks for information.
Usage.xhp tit help.text	Usage
Usage.xhp bm_id0603200910434044_scalc help.text	<bookmark_value>Solver for Nonlinear Problems;Usage</bookmark_value>
Usage.xhp hd_id0603200910430882 help.text	Usage
Usage.xhp par_id0603200910430845 help.text	Regardless whether you use DEPS or SCO, you start by going to <menuitem>Tools - Solver</menuitem> and set the Cell to be optimized, the direction to go (minimization, maximization) and the cells to be modified to reach the goal. Then you go to the Options and specify the solver to be used and if necessary adjust the according <link href="com.sun.star.comp.Calc.NLPSolver/Options.xhp">parameters</link>.
Usage.xhp par_id0603200910430821 help.text	There is also a list of constraints you can use to restrict the possible range of solutions or to penalize certain conditions. However, in case of the evolutionary solvers DEPS and SCO, these constraints are also used to specify bounds on the variables of the problem. Due to the random nature of the algorithms, it is <emph>highly recommended</emph> to do so and give upper (and in case "Assume Non-Negative Variables" is turned off also lower) bounds for all variables. They don't have to be near the actual solution (which is probably unknown) but should give a rough indication of the expected size (0 ≤ var ≤ 1 or maybe -1000000 ≤ var ≤ 1000000).
Usage.xhp par_id0603200910430873 help.text	Bounds are specified by selecting one or more variables (as range) on the left side and entering a numerical value (not a cell or a formula) on the right side. That way you can also choose one or more variables to be <emph>Integer</emph> or <emph>Binary</emph> only.
help.tree 08 help_section.text	Solver for Nonlinear Problems
help.tree 0816 node.text	Solver for Nonlinear Problems

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sat/nlpsolver/help/en/com.sun.star.comp.Calc.NLPSolver.po, string 41