This paper considers a class of stochastic vehicle routing problems (SVRPs) with random demands, in which the number of potential failures per route is restricted either by the data or the problem constraints. These are realistic cases as it makes little sense to plan vehicle routes that systematically fail a large number of times. First, a chance constrained version of the problem is considered which can be solved to optimality by algorithms similar to those developed for the deterministic vehicle routing problem (VRP). Three classes of SVRP with recourse are then analyzed. In all cases, route failures can only occur at one of the last k customers of the planned route. Since in general, SVRPs are considerably more intractable than the deterministic VRPs, it is interesting to note that these realistic stochastic problems can be solved as a sequence of deterministic traveling salesman problems (TSPs). In particular, when k=1 the SVRP with recourse reduces to a single TSP.
|Original language||English (US)|
|Number of pages||11|
|Journal||ZOR Zeitschrift für Operations Research Methods and Models of Operations Research|
|State||Published - Oct 1993|
ASJC Scopus subject areas
- Management Science and Operations Research