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Chips-n-Salsa is a Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms. The library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling. Chips-n-Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally. The library very extensively supports simulated annealing. It includes several classes for representing solutions to a variety of optimization problems. For example, the library includes a BitVector class that implements vectors of bits, as well as classes for representing solutions to problems where we are searching for an optimal vector of integers or reals. For each of the built-in representations, the library provides the most common mutation operators for generating random neighbors of candidate solutions, as well as common crossover operators for use with evolutionary algorithms. Additionally, the library provides extensive support for permutation optimization problems, including implementations of many different mutation operators for permutations, and utilizing the efficiently implemented Permutation class of the JavaPermutationTools (JPT) library. Chips-n-Salsa is customizable, making extensive use of Java's generic types, enabling using the library to optimize other types of representations beyond what is provided in the library. It is hybridizable, providing support for integrating multiple forms of local search (e.g., using a hill climber on a solution generated by simulated annealing), creating hybrid mutation operators (e.g., local search using multiple mutation operators), as well as support for running more than one type of search for the same problem concurrently using multiple threads as a form of algorithm portfolio. Chips-n-Salsa is iterative, with support for multistart metaheuristics, including implementations of several restart schedules for varying the run lengths across the restarts. It also supports parallel execution of multiple instances of the same, or different, stochastic local search algorithms for an instance of a problem to accelerate the search process. The library supports self-adaptive search in a variety of ways, such as including implementations of adaptive annealing schedules for simulated annealing, such as the Modified Lam schedule, implementations of the simpler annealing schedules but which self-tune the initial temperature and other parameters, and restart schedules that adapt to run length.

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/*
 * Chips-n-Salsa: A library of parallel self-adaptive local search algorithms.
 * Copyright (C) 2002-2022 Vincent A. Cicirello
 *
 * This file is part of Chips-n-Salsa (https://chips-n-salsa.cicirello.org/).
 *
 * Chips-n-Salsa is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * Chips-n-Salsa is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program.  If not, see .
 */

package org.cicirello.search.representations;

/**
 * A class for representing the input to a multivariate function, with real values (floating-point)
 * that are bounded in some interval [min, max].
 *
 * @author Vincent A. Cicirello, https://www.cicirello.org/
 */
public final class BoundedRealVector extends RealVector {

  private final double min;
  private final double max;

  /**
   * Initializes the vector to the specified values, subject to the given bounds [min, max].
   *
   * @param x The initial values for the vector. Any values that are less than min will instead be
   *     set to min. Any values that are greater than max will instead be set to max.
   * @param min The minimum allowed value for each integer.
   * @param max The maximum allowed value for each integer.
   * @throws IllegalArgumentException if min > max
   */
  public BoundedRealVector(double[] x, double min, double max) {
    super(x.length);
    if (min > max) throw new IllegalArgumentException("max must be greater than or equal to min");
    this.min = min;
    this.max = max;
    for (int i = 0; i < x.length; i++) {
      set(i, x[i]);
    }
  }

  /**
   * Copies a BoundedRealVector.
   *
   * @param other The other BoundedRealVector
   */
  public BoundedRealVector(BoundedRealVector other) {
    super(other);
    min = other.min;
    max = other.max;
  }

  /**
   * Sets a parameter to a specified value, subject to the lower and upper bounds for this function
   * input. If the specified new value is less than the min, then the function input is set to the
   * min. If the specified new value is greater than the max, then the function input is set to the
   * max. Otherwise, the function input is set to the specified value.
   *
   * @param i The input to set.
   * @param value The new value for the i-th function input.
   * @throws ArrayIndexOutOfBoundsException if i < 0 or i ≥ length().
   */
  @Override
  public final void set(int i, double value) {
    if (value < min) super.set(i, min);
    else if (value > max) super.set(i, max);
    else super.set(i, value);
  }

  /**
   * Sets from an array, subject to the lower and upper bounds for this vector. If a specified new
   * value is less than the min, then it is set to the min. If the specified new value is greater
   * than the max, then the it is set to the max. Otherwise, it is set to the specified value.
   *
   * @param values The values to set.
   */
  @Override
  public final void set(double[] values) {
    for (int i = 0; i < values.length; i++) {
      set(i, values[i]);
    }
  }

  /**
   * Checks if the bounds of this BoundedRealVector are the same as those of another.
   *
   * @param other The other vector.
   * @return true if the vectors have the same bounds and false otherwise
   */
  public final boolean sameBounds(BoundedRealVector other) {
    return min == other.min && max == other.max;
  }

  /**
   * Creates an identical copy of this object.
   *
   * @return an identical copy of this object
   */
  @Override
  public BoundedRealVector copy() {
    return new BoundedRealVector(this);
  }

  /**
   * Indicates whether some other object is "equal to" this one. To be equal, the other object must
   * be of the same runtime type and contain the same values and bounds.
   *
   * @param other The other object to compare.
   * @return true if other is not null, is of the same runtime type as this, and contains the same
   *     values and bounds.
   */
  @Override
  public boolean equals(Object other) {
    if (!super.equals(other) || !(other instanceof BoundedRealVector)) return false;
    return sameBounds((BoundedRealVector) other);
  }

  /**
   * Returns a hash code value.
   *
   * @return a hash code value
   */
  @Override
  public int hashCode() {
    return 31 * (31 * (31 + Double.hashCode(min)) + Double.hashCode(max)) + super.hashCode();
  }
}