Simulation based optimisation or simulation optimisation is an important field in stochastic optimisation. The present report introduces into that problem area. We distinguish between the non-recursive and recursive approaches of simulation optimisation. For the non-recursive approach we consider three methods, the retrospective, SPO-, and the RS-methods. With the help of a simple inventory problem we discuss the advantages and disadvantages of these methods. As a recursive method we consider in the second part of our report the coupling of simulation with Genetic Algorithms. As an application example we take a complex multi-location inventory model with lateral transshipments. From our experiences with such optimisation problems we finally...
A methodology for optimization of simulation models is presented. The methodology is based on a gene...
Widespread hard optimisation problems in economics and logistics are characterised by large dimensio...
Many systems in logistics can be adequately modeled using stochastic discrete event simulation model...
Simulation based optimisation or simulation optimisation is an important field in stochastic optimis...
Simulation based optimisation or simulation optimisation is an important field in stochastic optimis...
Simulation based optimisation or simulation optimisation is an important field in stochastic optimis...
Computer simulation models are widely and frequently used to model real systems to predict output re...
Simulation Optimization (SO) provides a structured approach to the system design and configuration w...
Simulation Optimization (SO) provides a structured approach to the system design and configuration w...
Simulation optimization is increasingly popular for solving complicated and mathematically intractab...
In this tutorial we consider the problem of finding the best set up to use for a system, where the o...
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation o...
The article depicts an evolutionary approach to simulation based optimization of a typical manufactu...
Simulation has become one of the most popular tools for the design and analysis of complex systems. ...
Simulation has become one of the most popular tools for the design and analysis of complex systems. ...
A methodology for optimization of simulation models is presented. The methodology is based on a gene...
Widespread hard optimisation problems in economics and logistics are characterised by large dimensio...
Many systems in logistics can be adequately modeled using stochastic discrete event simulation model...
Simulation based optimisation or simulation optimisation is an important field in stochastic optimis...
Simulation based optimisation or simulation optimisation is an important field in stochastic optimis...
Simulation based optimisation or simulation optimisation is an important field in stochastic optimis...
Computer simulation models are widely and frequently used to model real systems to predict output re...
Simulation Optimization (SO) provides a structured approach to the system design and configuration w...
Simulation Optimization (SO) provides a structured approach to the system design and configuration w...
Simulation optimization is increasingly popular for solving complicated and mathematically intractab...
In this tutorial we consider the problem of finding the best set up to use for a system, where the o...
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation o...
The article depicts an evolutionary approach to simulation based optimization of a typical manufactu...
Simulation has become one of the most popular tools for the design and analysis of complex systems. ...
Simulation has become one of the most popular tools for the design and analysis of complex systems. ...
A methodology for optimization of simulation models is presented. The methodology is based on a gene...
Widespread hard optimisation problems in economics and logistics are characterised by large dimensio...
Many systems in logistics can be adequately modeled using stochastic discrete event simulation model...