Simulated and fitted responses per experimental configuration

Only few (slightly) significant interaction effects can be found. A negative impact on the /3-service level occurs for a simultaneous extension of turnover capacities for O2 and Cs as well as the simultaneous extension of Styrene s turnover capacity in combination with extended RTC processing times. Negative two-way interaction effects are not to be expected whereas positive ones indicate an effective exploitation of extended capacities. Due to the fact that only 100 replications were performed it is presumed that the (slightly) significant two-way interaction effects are spurious and reflect a noise effect. 

A positive interaction effect on the total number of dispatched trains is observed for the simultaneous extension of Styrene s turnover capacity in combination with an extended RTC processing time. I.e. more trains are dispatched as RTCs can be handled faster. This might be an indication that the fleet of Styrene RTCs is too small. However, this 

Considering a situation, when a re-configuration of the existing SC should be evaluated, the decision for a potential re-configuration depends on the costs of the potential re-configurations as well as the predicted benefit of the corresponding performance effects. 

As an alternative to RSM, simulation responses can be used directly to explore the sample space of control variables. To do so, a lot of combinatorial optimization approaches were adapted for simulation optimization. In general, there are four main classes of methods that have shown a particular applicability in (multi-objective) simulation optimization Meta-heuristics, gradient-based procedures, random search, and sample path optimization. Of particular interest are meta-heuristics as they have shown a good performance for a wide range of combinatorial optimization approaches. Therefore, commercial simulation software primarily uses these techniques to incorporate simulation optimization routines. Among meta-heuristics, tabu search, scatter search, and genetic algorithms are most widely used. Table 4.13 provides an overview on aU aforementioned techniques. 

In non-commercial applications often genetic algorithms are proposed. In general, 

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