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Author: kyle cooper

README.md

@@ -11,6 +11,48 @@ We also include an implementation of R-SPLINE, which can be cited as follows:
 
 Wang, H., Pasupathy, R., and Schmeiser, B. W. 2013. Integer-ordered simulation optimization using R-SPLINE: Retrospective Search with Piecewise-Linear Interpolation and Neighborhood Enumeration. ACM Transactions on Modeling and Computer Simulation, Vol. 23, No. 3, Article 17 (July 2013), 24 pages. DOI:http://dx.doi.org/10.1145/2499913.2499916
 
+Table of Contents
+=================
+
+   * [PyMOSO](#pymoso)
+      * [Reference](#reference)
+      * [Installation](#installation)
+         * [Dependency: Python 3.6 ](#dependency-python-36)
+         * [Install from PyPI](#install-from-pypi)
+         * [Install latest trunk version from git](#install-latest-trunk-version-from-git)
+         * [Install from source](#install-from-source)
+      * [CLI](#cli)
+            * [listitems](#listitems)
+            * [solve](#solve)
+            * [testsolve](#testsolve)
+            * [Output](#output)
+            * [Table of options for solve and testsolve](#table-of-options-for-solve-and-testsolve)
+            * [Table of algorithm-specific parameters](#table-of-algorithm-specific-parameters)
+      * [Programming guide](#programming-guide)
+         * [Implementing a problem in PyMOSO](#implementing-a-problem-in-pymoso)
+            * [Template for implementing problems (myproblem.py)](#template-for-implementing-problems-myproblempy)
+            * [Using rng](#using-rng)
+            * [Simple example problem](#simple-example-problem)
+         * [Implementing a Tester in PyMOSO](#implementing-a-tester-in-pymoso)
+         * [Implementing algorithms in PyMOSO](#implementing-algorithms-in-pymoso)
+            * [Example MOSO algorithm in PyMOSO that uses RLE to ensure convergence (myaccel.py)](#example-moso-algorithm-in-pymoso-that-uses-rle-to-ensure-convergence-myaccelpy)
+            * [Example of an RA algorithm (myraalg.py)](#example-of-an-ra-algorithm-myraalgpy)
+            * [Example of a MOSO algorithm (mymoso.py)](#example-of-a-moso-algorithm-mymosopy)
+            * [PyMOSO internals](#pymoso-internals)
+               * [Table of PyMOSO internals](#table-of-pymoso-internals)
+               * [Table of chnutils functions](#table-of-chnutils-functions)
+            * [Useful snippets for implementing RA algorithms](#useful-snippets-for-implementing-ra-algorithms)
+               * [Sample a point](#sample-a-point)
+               * [Sample the point's neighbors](#sample-the-points-neighbors)
+               * [argsort the points by 1st objective](#argsort-the-points-by-1st-objective)
+               * [choose the minimizer and its objectives](#choose-the-minimizer-and-its-objectives)
+               * [Use SPLINE to get a local minimizer](#use-spline-to-get-a-local-minimizer)
+               * [Get the non-dominated subset of every visited point](#get-the-non-dominated-subset-of-every-visited-point)
+               * [Randomly choose points from the subset](#randomly-choose-points-from-the-subset)
+      * [Using PyMOSO in Python programs](#using-pymoso-in-python-programs)
+         * [Solve example](#solve-example)
+         * [TestSolve example](#testsolve-example)
+
 ## Installation
 ### Dependency: Python 3.6+
 This software requires Python 3.6 or higher. Python can be downloaded from https://www.python.org/downloads/.