1.1 --- a/org/lpsolve.org	Wed Nov 02 07:35:57 2011 -0700
     1.2 +++ b/org/lpsolve.org	Wed Nov 02 08:02:11 2011 -0700
     1.3 @@ -1,4 +1,4 @@
     1.4 -#+title: Discovering Effective Pokemon Types Using Linear Optimization
     1.5 +#+title: Discovering Effective Pok\eacute{}mon Types Using Linear Optimization
     1.6  #+author: Robert McIntyre & Dylan Holmes
     1.7  #+EMAIL:     rlm@mit.edu
     1.8  #+SETUPFILE: ../../aurellem/org/setup.org
     1.9 @@ -11,7 +11,7 @@
    1.10  locate the most effective Pok\eacute{}mon type
    1.11  combinations. Afterwards, we realized that we could transform this
    1.12  search problem into a /linear optimization problem/.  This conversion
    1.13 -offered several advantages: first, search algorithms are comparatively
    1.14 +offeres several advantages: first, search algorithms are comparatively
    1.15  slow, whereas linear optimization algorithms are extremely fast;
    1.16  second, it is difficult to determine whether a search problem has any
    1.17  solution, whereas it is straightforward to determine whether a linear
    1.18 @@ -28,7 +28,7 @@
    1.19        Clojure access to the linear programming C library, =lp_solve=.
    1.20   - Find effective Pokemon types using linear programming :: Building
    1.21        on our earlier code, (...)
    1.22 -- Present our results :: (!)
    1.23 +- Present our results :: 
    1.24   
    1.25  #which can be represented and solved as a system of linear equations.
    1.26    
    1.27 @@ -84,7 +84,7 @@
    1.28  
    1.29  ** The Farmer's Problem
    1.30  
    1.31 -Let's solve the Farmer's Problem, a typical linear programming problem
    1.32 +Let's solve the Farmer's Problem, an example linear programming problem
    1.33  borrowed from http://lpsolve.sourceforge.net/5.5/formulate.htm.
    1.34  
    1.35  
    1.36 @@ -139,7 +139,6 @@
    1.37  #1\end{bmatrix}\;\begin{bmatrix}w\\b\end{bmatrix}
    1.38  #\leq \begin{bmatrix}\$15000\\4000\text{ bushels}\\75\text{ acres}\end{bmatrix}\)
    1.39  
    1.40 -
    1.41  ** Solution using LP Solve
    1.42  #(LP solve is available at http://www.example.com.)
    1.43  In a new file,  =farmer.lp=, we list the variables and constraints