print.malschains

Print out some characteristics of a <code>malschains</code> result.
The result shows besides the best solution and its fitness the total number of evaluations spent for both EA and LS, 
the ratio of the spent evaluations (also called effort), the ratio of total improvement of the fitness,
the percentage of times that application of the EA/LS yielded improvement, and some timing results in milliseconds.

An implementation of an algorithm family for continuous
optimization called memetic algorithms with local search chains
(MA-LS-Chains), as proposed in Molina et al. (2010) <doi:10.1162/evco.2010.18.1.18102> and Molina et al. (2011) <doi:10.1007/s00500-010-0647-2>. Rmalschains is further discussed in Bergmeir et al. (2016) <doi:10.18637/jss.v075.i04>. Memetic algorithms are hybridizations of genetic
algorithms with local search methods. They are especially suited
for continuous optimization.

Christoph Bergmeir

Rmalschains

Continuous Optimization using Memetic Algorithms with Local
Search Chains (MA-LS-Chains)

José M. Benítez

Daniel Molina

Robert Davies

Dirk Eddelbuettel

Nikolaus Hansen

Richard J. Wagner

print.malschains function

<dl><dt>x</dt>
<dd>the <code>malschains</code> result</dd>
<dt>...</dt>
<dd>additional function parameters (currently not used)</dd></dl>

Arguments

Generic print function for malschains results — print.malschains

<dl>

<dt>x</dt>
<dd>the <code>malschains</code> result</dd>


<dt>...</dt>
<dd>additional function parameters (currently not used)</dd>

</dl>

print.malschains: Generic print function for malschains results

Description

Usage

Value

Arguments