13. Routing under Uncertainty: An Application in the Scheduling of Field Service Engineers

Traveling Salesman Problem: an Overview of Applications, Formulations, and Solution Approaches

“…The mTSP also appears to be a first stage problem in a two-stage solution procedure of a VRP with probabilistic service times. This is discussed further by (Hadjiconstantinou & Roberts, 2002). (Ralphs, 2003) mentions that the VRP instances arising in practice are very hard to solve, since the mTSP is also very complex.…”

Robust Vehicle Routing

“…The SVRP can be broadly classified based on the following three criteria: (1) where the uncertainty is present in the problem, e.g., the presence of the customers (Jézéquel [35], Jaillet [34], Bertsimas [9,10]), the demand level (Bertsimas and Simchi-Levi [13]), or the travel time (Kao [37], Laporte et al [40], Jula et al [36]) and the service time at customer sites (Hadjiconstantinou and Roberts [31]); (2) how the problem is modeled, e.g., by stochastic programming technique (Stewart and Golden [44], Bertsimas [10]), by Markov decision process (Dror and Trudeau [20], Dror [19], Dror et al [21], Secomandi [41]), or by robust optimization methodology (Sungur et al [45]); and (3) how to solve the model, which heavily depends on the modeling method and can be broadly classified into two categories: exact methods (branch and cut, integer L-shaped method (Gendreau et al [26]) and generalized dynamic programming (Carraway et al [16])) and heuristic methods such as saving algorithms (Clarke and Wright [17]), sweep algorithms, genetic algorithms, tabu search (Gendreau et al [28]) to name a few. For a more detailed discussion based on this classification, please refer to Shen et al [43].…”

“…An adaptation of the Clarke and Wright [17] savings algorithm is used for this problem. The VRP with stochastic service time was used in Hadjiconstantinou and Roberts [31] to model and solve a repair service. They used a two-stage recourse model and a paired tree search algorithm to solve it.…”

A two‐stage vehicle routing model for large‐scale bioterrorism emergencies

“…The stochastic vehicle routing problem can be broadly classified based on the following three criteria: (1) where the uncertainty lies in the problem, e.g., the presence of the customers [4,5,41,42] the demand level [6] or the travel time [44,45,47] and the service time at customer sites [38]; (2) how to model the problem, e.g., by stochastic programming technique [5,62], by Markov decision process [16,17,19,60] or by robust optimization methodology [63]; (3) how to solve the model, which heavily depends on the modeling method and can be broadly classified into two categories: exact methods (branch and cut, integer L-shape method [29] and generalized dynamic programming [11]) and heuristic methods such as saving algorithms [15], sweep algorithms, Genetic Algorithms, tabu search [31] to name a few. For a more detailed discussion based on this classification, please refer to Ref.…”