solveP1

Solve the network flow problem - twoDistMatch

Matching algorithm based on network-flow structure.
Users are able to modify the emphasis on three different
optimization goals: two different distance measures and
the number of treated units left unmatched. The method is proposed by Pimentel
and Kelz (2019) <doi:10.1080/01621459.2020.1720693>.
The 'rrelaxiv' package, which provides an alternative solver for
the underlying network flow problems, carries an
academic license and is not available on CRAN, but
may be downloaded from Github at
<https://github.com/josherrickson/rrelaxiv/>.

Shichao Han

MultiObjMatch

Multi-Objective Matching Algorithm

Samuel D. Pimentel

solveP1 function

<dl><dt>net</dt>
<dd>the network representation</dd>
<dt>f1.list</dt>
<dd>the list of the first objective functions values for
each node</dd>
<dt>f2.list</dt>
<dd>the list of the second objective functions values for
each node</dd>
<dt>f3.list</dt>
<dd>the list of the third objective functions values for
each node</dd>
<dt>rho1</dt>
<dd>the penalty coefficient for the second objective</dd>
<dt>rho2</dt>
<dd>the penalty coefficient for the third objective</dd>
<dt>tol</dt>
<dd>the tolerance value for precision</dd></dl>

Arguments

Solve the network flow problem - twoDistMatch — solveP1

<dl>

<dt>net</dt>
<dd>the network representation</dd>


<dt>f1.list</dt>
<dd>the list of the first objective functions values for
each node</dd>


<dt>f2.list</dt>
<dd>the list of the second objective functions values for
each node</dd>


<dt>f3.list</dt>
<dd>the list of the third objective functions values for
each node</dd>


<dt>rho1</dt>
<dd>the penalty coefficient for the second objective</dd>


<dt>rho2</dt>
<dd>the penalty coefficient for the third objective</dd>


<dt>tol</dt>
<dd>the tolerance value for precision</dd>

</dl>

solveP1: Solve the network flow problem - twoDistMatch

Description

Usage

Value

Arguments