The allocation of buffers in flow lines with stochastic processing times is an important decision in the
design of production systems. The aim is to minimize the overall number of buffer capacities obtaining at
least a goal production rate. We derive a mixed integer program by sampling the effective processing times.
The computation time with standard solvers becomes very long. To reduce the computation time, a Benders
Decomposition approach is developed. The master problem contains the binary variables of the original MIP
and the subproblem contains the real-valued decision variables only. Cuts are iteratively derived from the
subproblem and added to the master problem such that optimality is proven at the termination. This paper
discusses different cuts that influence the performance of the algorithm. Numerical experiments are carried
out in order to evaluate these influences.
Dieser Eintrag ist Teil der Universitätsbibliographie.
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