Monte-Carlo-Based Robust Procedure for Dynamic Line Layout Problems

Abstract

Carlo simulation techniques can be applied to map the distribution of volume distance values in the solution space corresponding to deterministic line layout problems is exploited to define stopping criteria for robust procedures. A line layout algorithm is proposed which uses these sampling procedures to first construct a mapping of the volume distance solution space for each parameter set, and then identify layouts meeting minimum performance standards for all potential operating scenarios.The next section describes uncertainty in the information base associated with line layout problems and describes previous work associated with solving stochastic problems and the empirical mapping of volume distance distributions. The third section describes a robust algorithm for solving the stochastic and/or dynamic line layout problem. In the fourth section, two test problems are introduced and computational experience with the procedure is described. The fifth section extends the study by allowing nonlinear material handling costs. The final section offers a summary and conclusions.