ILPObjective.java
package org.drip.linearprogram.canonical;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2020 Lakshmi Krishnamurthy
*
* This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
* asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
* analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
* equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
* numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
* and computational support.
*
* https://lakshmidrip.github.io/DROP/
*
* DROP is composed of three modules:
*
* - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
* - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
* - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
*
* DROP Product Core implements libraries for the following:
* - Fixed Income Analytics
* - Loan Analytics
* - Transaction Cost Analytics
*
* DROP Portfolio Core implements libraries for the following:
* - Asset Allocation Analytics
* - Asset Liability Management Analytics
* - Capital Estimation Analytics
* - Exposure Analytics
* - Margin Analytics
* - XVA Analytics
*
* DROP Computational Core implements libraries for the following:
* - Algorithm Support
* - Computation Support
* - Function Analysis
* - Model Validation
* - Numerical Analysis
* - Numerical Optimizer
* - Spline Builder
* - Statistical Learning
*
* Documentation for DROP is Spread Over:
*
* - Main => https://lakshmidrip.github.io/DROP/
* - Wiki => https://github.com/lakshmiDRIP/DROP/wiki
* - GitHub => https://github.com/lakshmiDRIP/DROP
* - Repo Layout Taxonomy => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
* - Javadoc => https://lakshmidrip.github.io/DROP/Javadoc/index.html
* - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
* - Release Versions => https://lakshmidrip.github.io/DROP/version.html
* - Community Credits => https://lakshmidrip.github.io/DROP/credits.html
* - Issues Catalog => https://github.com/lakshmiDRIP/DROP/issues
* - JUnit => https://lakshmidrip.github.io/DROP/junit/index.html
* - Jacoco => https://lakshmidrip.github.io/DROP/jacoco/index.html
*
* 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.
*/
/**
* <i>ILPObjective</i> holds the Coefficients of the Objective Term of an Integer Linear Program
* c<sup>T</sup>x where c is R<sup>n</sup> and x is Z<sub>+</sub><sup>n</sup>. The References are:
*
* <br><br>
* <ul>
* <li>
* Burdet, C. A., and E. L. Johnson (1977): A Sub-additive Approach to Solve Linear Integer Programs
* <i>Annals of Discrete Mathematics</i> <b>1</b> 117-143
* </li>
* <li>
* Chvatal, V. (1973): Edmonds Polytopes in a Hierarchy of Combinatorial Problems <i>Discrete
* Mathematics</i> <b>4 (4)</b> 305-337
* </li>
* <li>
* Gomory, R. E. (1958): Outline of an Algorithm for Integer Solutions to Linear Programs
* <i>Bulletin of the American Mathematical Society</i> <b>64 (5)</b> 275-278
* </li>
* <li>
* Kelley, J. E. (1960): The Cutting Plane Method for Solving Convex Problems <i>Journal for the
* Society of the Industrial and Applied Mathematics</i> <b>8 (4)</b> 703-712
* </li>
* <li>
* Letchford, A. N. and A. Lodi (2002): Strengthening Chvatal-Gomory Cuts and Gomory Fractional Cuts
* <i>Operations Research Letters</i> <b>30 (2)</b> 74-82
* </li>
* </ul>
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/PortfolioCore.md">Portfolio Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/AssetAllocationAnalyticsLibrary.md">Asset Allocation Analytics</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/linearprogram/README.md">Linear Programming Solution Suite</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/linearprogram/canonical/README.md">Linear Programming Framework Canonical Elements</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class ILPObjective
{
private double[] _c = null;
/**
* ILPObjective Constructor
*
* @param c The Objective Coefficient Array
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public ILPObjective (
final double[] c)
throws java.lang.Exception
{
if (null == (_c = c))
{
throw new java.lang.Exception (
"ILPObjective Constructor => Invalid Inputs"
);
}
int dimension = _c.length;
if (0 == dimension)
{
throw new java.lang.Exception (
"ILPObjective Constructor => Invalid Inputs"
);
}
for (int dimensionIndex = 0;
dimensionIndex < dimension;
++dimensionIndex)
{
if (!org.drip.numerical.common.NumberUtil.IsValid (
_c[dimensionIndex]
))
{
throw new java.lang.Exception (
"ILPObjective Constructor => Invalid Inputs"
);
}
}
}
/**
* Retrieve "c"
*
* @return c
*/
public double[] c()
{
return _c;
}
/**
* Retrieve the Variate Dimension
*
* @return Variate Dimension
*/
public int dimension()
{
return _c.length;
}
/**
* Validate the Variate Input
*
* @param variateArray The Input Variate Array
*
* @return TRUE - The Input Variate successfully Validated
*/
public boolean validate (
final int[] variateArray)
{
if (null == variateArray)
{
return false;
}
int dimension = _c.length;
if (dimension != variateArray.length)
{
return false;
}
for (int dimensionIndex = 0;
dimensionIndex < dimension;
++dimensionIndex)
{
if (0 >= variateArray[dimensionIndex])
{
return false;
}
}
return true;
}
/**
* Evaluate the Objective Function at the specified Variate Array
*
* @param variateArray The Input Variate Array
*
* @return The Objective Function at the specified Variate Array
*
* @throws java.lang.Exception Thrown if the Evaluation cannot be done
*/
public double evaluate (
final int[] variateArray)
throws java.lang.Exception
{
if (!validate (
variateArray
))
{
throw new java.lang.Exception (
"ILPObjective::evaluate => Variate Array not Valid"
);
}
double value = 0.;
int dimension = _c.length;
for (int dimensionIndex = 0;
dimensionIndex < dimension;
++dimensionIndex)
{
value += _c[dimensionIndex] * variateArray[dimensionIndex];
}
return value;
}
}