Tourenplanung mit stochastischer korrelierter Nachfrage

Jacqueline Wirnitzer
In practice, many parameters of truck scheduling problems are inherently uncertain. Thus, many extensions of the basic Vehicle Routing Problem (VRP) have been established. One of them is the VRP with Stochastic Demands (VRPSD). Almost all published models solving this optimization problem assume independency between demand distributions of customers, although this assumption does not apply for many cases in reality. In this work, a generalisation of the VRPSD is introduced, in which correlation between customers is taken into account. We call this problem VRP with Correlated Stochastic Demand (VRPCSD). The aim of this thesis is to develop a two-stage heuristic solution to the problem. A regular tour schedule is created on the basis of stochastic data before actual demands are announced. Afterwards, when demands are known, the tour schedule is checked for infeasibilities and adjusted by recourse strategies if necessary. The overall objective is to minimize total costs. We refrain from reoptimisation (replanning when demands are announced) to save costs by regularities in tours (see Gröer, Golden und Wasil (2009)). In this work various methods and recourse strategies for the VRPCSD are developed. An improved Savings heuristic is the basis of this process. To create a regular tour schedule, the only approach to the VRPCSD found in literature is implemented and refined (Yee and Golden (1979)). Both the original and the adapted approach turn out to be inefficient, therefore, new methods are developed. Likewise, new recourse strategies are developed besides the established Back-To-Depot strategy. Finally, the various methods are combined with the recourse strategies and experiments are conducted. As a benchmark we use the average reoptimisation results. The best combinations of methods and recourse strategies achieve results that differ on average less than 20% from the benchmark.
Betreuer intern
Kai Furmans, Felix Brandt
Betreuer extern
Gudrun Thäter
Logistik und Supply-Chain-Optimierung
Download .bib
Download .bib
Eingetragen von
Felix Brandt