dotnet: Remove reference to dotnet release command
- Currently not implemented... Add abseil patch - Add patches/absl-config.cmake Makefile: Add abseil-cpp on unix - Force abseil-cpp SHA1 to 45221cc note: Just before the PR #136 which break all CMake Makefile: Add abseil-cpp on windows - Force abseil-cpp SHA1 to 45221cc note: Just before the PR #136 which break all CMake CMake: Add abseil-cpp - Force abseil-cpp SHA1 to 45221cc note: Just before the PR #136 which break all CMake port to absl: C++ Part - Fix warning with the use of ABSL_MUST_USE_RESULT > The macro must appear as the very first part of a function declaration or definition: ... Note: past advice was to place the macro after the argument list. src: dependencies/sources/abseil-cpp-master/absl/base/attributes.h:418 - Rename enum after windows clash - Remove non compact table constraints - Change index type from int64 to int in routing library - Fix file_nonport compilation on windows - Fix another naming conflict with windows (NO_ERROR is a macro) - Cleanup hash containers; work on sat internals - Add optional_boolean sub-proto Sync cpp examples with internal code - reenable issue173 after reducing number of loops port to absl: Python Part - Add back cp_model.INT32_MIN|MAX for examples Update Python examples - Add random_tsp.py - Run words_square example - Run magic_square in python tests port to absl: Java Part - Fix compilation of the new routing parameters in java - Protect some code from SWIG parsing Update Java Examples port to absl: .Net Part Update .Net examples work on sat internals; Add C++ CP-SAT CpModelBuilder API; update sample code and recipes to use the new API; sync with internal code Remove VS 2015 in Appveyor-CI - abseil-cpp does not support VS 2015... improve tables upgrade C++ sat examples to use the new API; work on sat internals update license dates rewrite jobshop_ft06_distance.py to use the CP-SAT solver rename last example revert last commit more work on SAT internals fix
This commit is contained in:
@@ -23,9 +23,12 @@ package operations_research;
|
||||
// First solution strategies, used as starting point of local search.
|
||||
message FirstSolutionStrategy {
|
||||
enum Value {
|
||||
// See the homonymous value in LocalSearchMetaheuristic.
|
||||
UNSET = 0;
|
||||
|
||||
// Lets the solver detect which strategy to use according to the model being
|
||||
// solved.
|
||||
AUTOMATIC = 0;
|
||||
AUTOMATIC = 15;
|
||||
|
||||
// --- Path addition heuristics ---
|
||||
// Starting from a route "start" node, connect it to the node which produces
|
||||
@@ -72,14 +75,20 @@ message FirstSolutionStrategy {
|
||||
// optional nodes (with finite penalty costs).
|
||||
BEST_INSERTION = 7;
|
||||
// Iteratively build a solution by inserting the cheapest node at its
|
||||
// cheapest position; the cost of insertion is based on the the arc cost
|
||||
// cheapest position; the cost of insertion is based on the arc cost
|
||||
// function. Is faster than BEST_INSERTION.
|
||||
PARALLEL_CHEAPEST_INSERTION = 8;
|
||||
// Iteratively build a solution by constructing routes sequentially, for
|
||||
// each route inserting the cheapest node at its cheapest position until the
|
||||
// route is completed; the cost of insertion is based on the arc cost
|
||||
// function. Is faster than PARALLEL_CHEAPEST_INSERTION.
|
||||
SEQUENTIAL_CHEAPEST_INSERTION = 14;
|
||||
// Iteratively build a solution by inserting each node at its cheapest
|
||||
// position; the cost of insertion is based on the the arc cost function.
|
||||
// position; the cost of insertion is based on the arc cost function.
|
||||
// Differs from PARALLEL_CHEAPEST_INSERTION by the node selected for
|
||||
// insertion; here nodes are considered in their order of creation. Is
|
||||
// faster than PARALLEL_CHEAPEST_INSERTION.
|
||||
// insertion; here nodes are considered in decreasing order of distance to
|
||||
// the start/ends of the routes, i.e. farthest nodes are inserted first.
|
||||
// Is faster than SEQUENTIAL_CHEAPEST_INSERTION.
|
||||
LOCAL_CHEAPEST_INSERTION = 9;
|
||||
|
||||
// --- Variable-based heuristics ---
|
||||
@@ -100,8 +109,13 @@ message FirstSolutionStrategy {
|
||||
// descent, they will try to escape local minima.
|
||||
message LocalSearchMetaheuristic {
|
||||
enum Value {
|
||||
// Means "not set". If the solver sees that, it'll behave like for
|
||||
// AUTOMATIC. But this value won't override others upon a proto MergeFrom(),
|
||||
// whereas "AUTOMATIC" will.
|
||||
UNSET = 0;
|
||||
|
||||
// Lets the solver select the metaheuristic.
|
||||
AUTOMATIC = 0;
|
||||
AUTOMATIC = 6;
|
||||
|
||||
// Accepts improving (cost-reducing) local search neighbors until a local
|
||||
// minimum is reached.
|
||||
@@ -116,8 +130,9 @@ message LocalSearchMetaheuristic {
|
||||
// Uses tabu search to escape local minima
|
||||
// (cf. http://en.wikipedia.org/wiki/Tabu_search).
|
||||
TABU_SEARCH = 4;
|
||||
// Uses tabu search on the objective value of solution to escape local
|
||||
// minima
|
||||
OBJECTIVE_TABU_SEARCH = 5;
|
||||
// Uses tabu search on a list of variables to escape local minima. The list
|
||||
// of variables to use must be provided via the SetTabuVarsCallback
|
||||
// callback.
|
||||
GENERIC_TABU_SEARCH = 5;
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user