Commit 5906fd7a authored by Markus Klinik's avatar Markus Klinik
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related work: IMOPSE

parent a450ba00
\section{Related Work}
Our work combines and extends existing work.
Our chromosome encoding scheme of assignments and the greedy schedule builder are inspired by the implementation by \citet{MyszkowskiLNS2018}.
They have a Java implementation of a genetic algorithm that solves the MSRCPSP with fixed costs, called salaries.
They optimize total cost and makespan.
In their version of the MSRCPSP, one task has exactly one capability requirement, whereas our tasks can have multiple.
One consequence of this is that their chromosomes always encode valid solutions, while our chromosomes might encode invalid solutions, where not all capability requirements can have a resource assigned.
We therefore had to add a measure of invalidity to our fitness function, that gives a negative score to solutions depending on the number of unassigned capability requirements.
Furthermore, our work extends theirs with user-defined capability functions and resource affinity constraints.
\begin{itemize}[noitemsep]
\item Support for invalid chromosomes
\item Support for environment being passed to fitness function
\item Elitist preservation
\item Fitness function returns a list of objectives, tagged as either less-is-better or more-is-better
\item Support for weights in the objective list
\end{itemize}
\begin{itemize}[noitemsep]
\item IMOPSE
\item simple-genetic-algorithm https://hackage.haskell.org/package/simple-genetic-algorithm https://github.com/afiskon/simple-genetic-algorithm
\item Deb, Kalyanmoy, et al. “A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II.” International Conference on Parallel Problem Solving From Nature. Springer Berlin Heidelberg, 2000
\item Bellenguez-Morineau and Neron
\item Artigues Book
\item Almeida, Correia, Da-Gama
......
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