Files
ortools-clone/examples/contrib/Diet.java
Corentin Le Molgat b027e57e95 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
2018-11-30 14:48:55 +01:00

95 lines
2.8 KiB
Java

// Copyright 2011 Hakan Kjellerstrand hakank@gmail.com
// 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.
import com.google.ortools.constraintsolver.*;
import com.google.ortools.constraintsolver.DecisionBuilder;
import com.google.ortools.constraintsolver.IntVar;
import com.google.ortools.constraintsolver.Solver;
import java.io.*;
import java.text.*;
import java.util.*;
public class Diet {
static {
System.loadLibrary("jniortools");
}
/** Solves the Diet problem. See http://www.hakank.org/google_or_tools/diet1.py */
private static void solve() {
Solver solver = new Solver("Diet");
int n = 4;
int[] price = {50, 20, 30, 80}; // in cents
// requirements for each nutrition type
int[] limits = {500, 6, 10, 8};
// nutritions for each product
int[] calories = {400, 200, 150, 500};
int[] chocolate = {3, 2, 0, 0};
int[] sugar = {2, 2, 4, 4};
int[] fat = {2, 4, 1, 5};
//
// Variables
//
IntVar[] x = solver.makeIntVarArray(n, 0, 100, "x");
IntVar cost = solver.makeScalProd(x, price).var();
//
// Constraints
//
solver.addConstraint(solver.makeScalProdGreaterOrEqual(x, calories, limits[0]));
solver.addConstraint(solver.makeScalProdGreaterOrEqual(x, chocolate, limits[1]));
solver.addConstraint(solver.makeScalProdGreaterOrEqual(x, sugar, limits[2]));
solver.addConstraint(solver.makeScalProdGreaterOrEqual(x, fat, limits[3]));
//
// Objective
//
OptimizeVar obj = solver.makeMinimize(cost, 1);
//
// Search
//
DecisionBuilder db = solver.makePhase(x, solver.CHOOSE_PATH, solver.ASSIGN_MIN_VALUE);
solver.newSearch(db, obj);
while (solver.nextSolution()) {
System.out.println("cost: " + cost.value());
System.out.print("x: ");
for (int i = 0; i < n; i++) {
System.out.print(x[i].value() + " ");
}
System.out.println();
}
solver.endSearch();
// Statistics
System.out.println();
System.out.println("Solutions: " + solver.solutions());
System.out.println("Failures: " + solver.failures());
System.out.println("Branches: " + solver.branches());
System.out.println("Wall time: " + solver.wallTime() + "ms");
}
public static void main(String[] args) throws Exception {
Diet.solve();
}
}