Changes between Version 51 and Version 52 of Orio

Timestamp:

06/13/08 02:00:20 (15 years ago)

Author:

hartono

Comment:

--

Orio

@@ -215 +215 @@
 A search technique sometimes has several parameters that need to be specified. For instance, the Nelder-Mead Simplex algorithm necessitates four kinds of coefficients: ''reflection'', ''expansion'', ''contraction'', and ''shrinkage''; and all of these coefficients have default values already defined in the Orio implementation. To alter the values of these algorithm-specific parameters, users can optionally specify them in the tuning specifications. In the example presented above, all arguments with names that start with `simplex_` are called search parameters specifically designed to steer the Simplex algorithm. 
 
-To further improve the quality of the search result, each search heuristic is enhanced by applying a local search after the search completes. The local search compares the best performance with neighboring coordinates. If a better coordinate is discovered, the local search continues recursively until no further improvement is possible.  In the previous example, users can adjust the distance of the local search by modifying the value of the argument ''simplex_local_distance''. A local distance of two implies that the local search examines the performances of all neighbors within a distance of two.
-
-The following table lists all information about the search techniques implemented in the Orio's search engine.
-
-|| '''Search technique''' || '''Algorithm-specific arguments''' || '''Argument's default value''' || 
-|| ''Exhaustive'' || - || - ||
-|| ''Random'' || - || - ||
-|| ''Nelder-Mead simplex'' || `local_distance` (i.e. the maximum distance of neighboring coordinates considered by the local search) [[BR]] `reflection_coef` [[BR]] `expansion_coef` [[BR]] `contraction_coef` [[BR]] `shrinkage_coef` || - ||
-|| ''Simulated annealing'' || - || - ||
+To further improve the quality of the search result, each search heuristic is enhanced by applying a local search after the search completes. The local search compares the best performance with neighboring coordinates. If a better coordinate is discovered, the local search continues recursively until no further improvement is possible.  In the previous example, users can adjust the distance of the local search by modifying the value of the argument ''simplex_local_distance''. A local distance of two implies that the local search examines the performances of all neighbors within a distance of two. It is important to note that the local search is turned off by default for all search heuristics. Thus to activate the local search, Orio users must explicitly assign a positive integer value to the ''local_distance'' algorithm-specific argument.
+
+The following table lists information about the search techniques implemented in the Orio's search engine.
+
+|| '''Search technique''' || '''Keyword''' || '''Algorithm-specific arguments''' || '''Default values''' || '''Argument description''' ||
+|| ''Exhaustive'' || '`Exhaustive`' || - || - ||
+|| ''Random'' || '`Random`' || `local_distance` || 0 || the maximum distance of neighboring coordinates considered by the local search ||
+|| ''Nelder-Mead simplex'' || '`Simplex`' || `local_distance` [[BR]] `reflection_coef` [[BR]] `expansion_coef` [[BR]] `contraction_coef` [[BR]] `shrinkage_coef` || 0 [[BR]] 1.0 [[BR]] 2.0 [[BR]] 0.5 [[BR]] 0.5 || the maximum distance of neighboring coordinates considered by the local search [[BR]]
+|| ''Simulated annealing'' || '`Annealing`' || `local_distance` [[BR]] `cooling_factor` [[BR]] `final_temperature_ratio` [[BR]] `trials_limit` [[BR]] `moves_limit` || 0 [[BR]] 0.95 [[BR]] 0.05 [[BR]] 100 [[BR]] 20 || the maximum distance of neighboring coordinates considered by the local search [[BR]] the temperature reduction factor [[BR]] the percentage of the temperature used as a termination criterion
+
+(i.e. )
 
 == Developer Guide ==