Simulation-Based Optimization with HeuristicLab: Practical Guidelines and Real-World Applications
Sprache des Titels:
Englisch
Original Buchtitel:
Applied Simulation and Optimization
Original Kurzfassung:
Dynamic and stochastic problem environments are often difficult tomodel
using standard problem formulations and algorithms. One way to model and then
solve them is simulation-based optimization: Simulations are integrated into the optimization
process in order to evaluate the quality of solution candidates and to identify
optimized system configurations. Potential solutions are evaluated with a simulation
model, which leads to new challenges regarding runtime performance, robustness,
and distributed evaluation. In order to design, compare, and parameterize algorithmic
approaches it is beneficial to use an optimization framework for algorithm design
and evaluation. On the one hand, this chapter shows how arbitrary simulators can be
coupled with the open-source HeuristicLab optimization framework. This coupling
is implemented in a generic way so that the simulators act as external evaluators. On
the other hand, we demonstrate how arbitrary optimizers available within HeuristicLab
can be called from a simulator in order to perform complex optimization
tasks within the simulation model. In order to illustrate the applicability of these
approaches, real-world examples investigated by the authors are discussed.We show
here application examples from different fields, namely logistics network design,
vendor managed inventory routing, steel slab logistics, production optimization with
dispatching rule scheduling, material flow simulation, and layout optimization.
Sprache der Kurzfassung:
Englisch
Veröffentlicher:
Springer International Publishing
Verlagsanschrift:
Springer International Publishing Switzerland
Erscheinungsjahr:
2015
ISBN:
978-3-319-15033-8
Anzahl der Seiten:
323
Reichweite:
international
Publikationstyp:
Fachbuch als Band einer Schriftenreihe/Serie (Erstauflage)
Forschungs-