A graph-based framework for model-driven optimization facilitating impact analysis of mutation operator properties
Optimization problems in software engineering typically deal with structures as they occur in
the design and maintenance of software systems. In model-driven optimization (MDO) …
the design and maintenance of software systems. In model-driven optimization (MDO) …
A generic construction for crossovers of graph-like structures and its realization in the eclipse modeling framework
In model-driven optimization (MDO), domain-specific models are used to define and solve
optimization problems via meta-heuristic search, often via evolutionary algorithms. Models …
optimization problems via meta-heuristic search, often via evolutionary algorithms. Models …
A multiplicity-preserving crossover operator on graphs
H Thölke, J Kosiol - Proceedings of the 25th International Conference on …, 2022 - dl.acm.org
Evolutionary algorithms usually explore a search space of solutions by means of crossover
and mutation. While a mutation consists of a small, local modification of a solution, crossover …
and mutation. While a mutation consists of a small, local modification of a solution, crossover …
Model-Driven Optimization: Towards Performance-Enhancing Low-Level Encodings
L Van Arragon, CD Damasceno… - 2023 ACM/IEEE …, 2023 - ieeexplore.ieee.org
In Model-Driven Optimisation, meta-heuristic opti-mization algorithms are applied to models
to solve optimization problems. A meta-model is used to describe a modelling language …
to solve optimization problems. A meta-model is used to describe a modelling language …
On the Application of Model-Driven Optimization to Business Processes
The optimization of business processes is an important task to increase the efficiency of the
described workflows. Metaheuristic optimization, such as evolutionary search, has been …
described workflows. Metaheuristic optimization, such as evolutionary search, has been …
A multiplicity-preserving crossover operator on graphs. Extended version
H Thölke, J Kosiol - arxiv preprint arxiv:2208.10881, 2022 - arxiv.org
Evolutionary algorithms usually explore a search space of solutions by means of crossover
and mutation. While a mutation consists of a small, local modification of a solution, crossover …
and mutation. While a mutation consists of a small, local modification of a solution, crossover …
Model-Driven Optimization with a Focus on the Effectiveness and Efficiency of Evolutionary Algorithms
S John - 2023 - archiv.ub.uni-marburg.de
Optimization problems are ubiquitous in software engineering. They arise, for example,
when searching for a modular software design or planning a cost-efficient development …
when searching for a modular software design or planning a cost-efficient development …
On the Application of Model-Driven Optimization to Business Processes
J Kosiol, L Lambers - Application and Theory of Petri Nets and … - books.google.com
The optimization of business processes is an important task to increase the efficiency of the
described workflows. Metaheuristic optimization, such as evolutionary search, has been …
described workflows. Metaheuristic optimization, such as evolutionary search, has been …