set_cover.proto

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// Copyright 2010-2024 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
 
syntax = "proto3";
 
package operations_research;
 
import "ortools/util/int128.proto";
 
option java_package = "com.google.ortools.algorithms";
option java_multiple_files = true;
 
message SetCoverProto {
  message Subset {
    // The cost for using the given subset.
    optional double cost = 1;
 
    // The list of elements in the subset.
    repeated int32 element = 2 [packed = true];
  }
 
  // The list of subsets in the model.
  repeated Subset subset = 1;
 
  // A user-defined name for the model.
  optional string name = 2;
 
  // An automatically fingerprint for the model. TODO(user): Implement.
  optional Int128 fingerprint = 3;
}
 
message SetCoverSolutionResponse {
  // Result of the optimization.
  enum Status {
    // Undefined.
    UNDEFINED = 0;
    // The solver found the proven optimal solution.
    OPTIMAL = 1;
    // The solver had enough time to find some solution that satisfied all
    // constraints, but it did not reach the optimal.
    FEASIBLE = 2;
    // The model does not have any solution.
    INFEASIBLE = 3;
    // The model is invalid.
    INVALID = 4;
  }
  // For future use. TODO(user): Implement.
  optional Status status = 1;
 
  // The number of subsets that are selected in the solution. This is used
  // to decompress their indices below.
  optional int32 num_subsets = 2;
 
  // The list of the subsets selected in the solution.
  repeated int32 subset = 3 [packed = true];
 
  // The cost of the solution, as computed by the algorithm.
  optional double cost = 4;
 
  // A lower bound of the solution, as computed by the algorithm.
  optional double cost_lower_bound = 5;
 
  // An automatically fingerprint for the solution. TODO(user): Implement.
  optional Int128 fingerprint = 6;
 
  // A reference to the model the solution applies to. TODO(user): Implement.
  optional Int128 model_fingerprint = 7;
}