The Vehicle Routing Problem with Stochastic Travel Times

Laporte, Gilbert; Louveaux, François; Mercure, Hélène

doi:10.1287/trsc.26.3.161

Cited by 330 publications

(146 citation statements)

References 12 publications

Supporting

Mentioning

142

Contrasting

Unclassified

Order By: Relevance

“…Considering a VRP with stochastic travel times and service times, Laporte et al [15] presented a chance constrained formulation as well as two recourse formulations. The recourse problem was solved to optimality for up to 20 nodes and 5 scenarios using an integer L-shaped method.…”

Section: Problem Description and Literature Reviewmentioning

confidence: 99%

“…Constraints (14) impose lower and upper limits on the unloaded quantities. Constraints (15) ensure that if ship v visits port arrival (i, m), then at least one product must be (un)loaded. Constraints (16) ensure that the sum of delivered goods should not be less than the sum of the consumption over the entire horizon T. Constraints (17) ensure that if ship v (un)loads one product at visit (i, m), then w imv must be one.…”

Section: Loading and Unloading Constraintsmentioning

confidence: 99%

See 1 more Smart Citation

A maritime inventory routing problem with stochastic sailing and port times

Agra

Christiansen

Delgado

et al. 2015

Computers & Operations Research

View full text Add to dashboard Cite

We consider a stochastic short sea shipping problem where a company is responsible for both the distribution of oil products between islands and the inventory management of those products at unloading ports. Ship routing and scheduling is associated to uncertainty in weather conditions and unpredictable waiting times in ports, and in this work, both sailing times and port times are considered to be stochastic parameters.A two-stage stochastic programming model with recourse is presented where the first-stage consists of routing, loading and unloading decisions, and the second stage consists of scheduling decisions. The model is solved using a decomposition approach similar to an L-shaped algorithm where optimality cuts are added dynamically, and this solution process is embedded within the sample average approximation method. A computational study based on ten real-world instances is presented.

show abstract

Section: Problem Description and Literature Reviewmentioning

confidence: 99%

Section: Loading and Unloading Constraintsmentioning

confidence: 99%

A maritime inventory routing problem with stochastic sailing and port times

Agra

Christiansen

Delgado

et al. 2015

Computers & Operations Research

View full text Add to dashboard Cite

show abstract

“…Carraway et al [13] used a generalized dynamic programming methodology to solve the TSPSTT. Laporte, Louveaux and Mercure [36] performed systematic research on the VRP with stochastic service and travel time (VRPSSTT). They proposed three models for the VRPSSTT: chance constrained model, 3-index recourse model, and 2-index recourse model.…”

Section: Svrps With Stochastic Travel Time and Service Timementioning

confidence: 99%

The Stochastic Vehicle Routing Problem for Minimum Unmet Demand

Shen

Ordóñez

Dessouky

2009

Springer Optimization and Its Applications

View full text Add to dashboard Cite

Summary. In this paper, we are interested in routing vehicles to minimize unmet demand with uncertain demand and travel time parameters. Such a problem arises in situations with large demand or tight deadlines, so that routes that satisfy all demand points are difficult or impossible to obtain. An important application is the distribution of medical supplies to respond to large-scale emergencies, such as natural disasters or terrorist attacks. We present a chance constrained formulation of the problem that is equivalent to a deterministic problem with modified demand and travel time parameters, under mild assumptions on the distribution of stochastic parameters; and relate it with a robust optimization approach. A tabu heuristic is proposed to solve this MIP and simulations are conducted to evaluate the quality of routes generated from both deterministic and chance constrained formulations. We observe that chance constrained routes can reduce the unmet demand by around 2%-6% for moderately tight deadline and total supply constraints.

show abstract

“…Jaillet (1988) introduced the a priori solution approach to the probabilistic TSP with stochastic customer requests (when the truck leaves the depot, there is uncertainty regarding what set of customers have to be served), later generalized to the VRP with stochastic customers and demand (Gendreau et al, 1996, Bertsimas et al, 1990, Jaillet and Odoni, 1988. Stochastic travel times in vehicle routing problems were introduced in Stewart and Golden (1983) and analyzed further in Laporte et al (1992) under general stochastic programming formulations (e.g. using chance constraints).…”

Section: Vrp Background Reviewmentioning

confidence: 99%

Pricing in Dynamic Vehicle Routing Problems

Figliozzi

Mahmassani

Jaillet

2007

Transportation Science

View full text Add to dashboard Cite

ABSTRACT:The principal focus of this paper is to study carrier pricing decisions for a new type of vehicle routing problems defined in a competitive and dynamic environment. This paper introduces the Vehicle Routing Problem in a Competitive Environment (VRPCE), as an extension of the Traveling Salesman Problem with Profits (TSPP) to a dynamic competitive auction environment. In the VRPCE, the carrier must estimate the incremental cost of servicing new service requests as they arrive dynamically. The paper presents a rigorous and precise treatment of the sequential pricing and costing problem that a carrier faces in such an environment. The sequential pricing problem presented here is an intrinsic feature of a sequential auction problem. In addition to introducing the formulation of this class of problems and discussing the main sources of difficulty in devising a solution, a simple example is constructed to show that carriers' prices under first price auction payment rules do not necessarily reflect the cost of servicing transportation requests. An approximate solution approach with a finite look-ahead horizon is presented and illustrated through numerical experiments, in competition with a static approach with no look-ahead.

show abstract

The Vehicle Routing Problem with Stochastic Travel Times

Cited by 330 publications

References 12 publications

A maritime inventory routing problem with stochastic sailing and port times

A maritime inventory routing problem with stochastic sailing and port times

The Stochastic Vehicle Routing Problem for Minimum Unmet Demand

Pricing in Dynamic Vehicle Routing Problems

Contact Info

Product

Resources

About