A branch‐and‐cut algorithm for the pickup and delivery traveling salesman problem with multiple stacks

Côté, Jean-François; Archetti, Claudia; Speranza, Maria; Gendreau, Michel; Potvin, Jean-Yves

doi:10.1002/net.21459

Cited by 27 publications

(52 citation statements)

References 33 publications

(97 reference statements)

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“…Formulations for the TSPPD with LIFO loading are presented by Arbib et al (2009) and Cordeau et al (2010), while a formulation for the TSPPD with FIFO loading is presented by Erdogan et al (2009) and Cordeau et al (2010b). Côté et al (2012b) present a formulation for the TSPPD with multiple stacks and LIFO loading. Øvstebø et al (2011) give a formulation for the TSP on roll-on/roll-off (RoRo) ships.…”

Section: Traveling Salesman Problem With Pickups and Deliveries With mentioning

confidence: 98%

“…A LNS is proposed to solve the problem heuristically. Côté et al (2012b) propose a branch-and-cut algorithm for the same problem and are able to solve instances with up to 43 vertices. Øvstebø et al (2011) examine a similar problem on roll-on/roll-off (RoRo) ships that transport cargo on wheels.…”

Section: Traveling Salesman Problem With Pickups and Deliveries With mentioning

confidence: 99%

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Vehicle routing problems with loading constraints: state-of-the-art and future directions

et al. 2014

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Distributors are faced with loading constraints in their route planning, e.g.,multi-dimensional packing constraints, unloading sequence constraints, stability constraints and axle weight limits. Ignoring these constraints impairs planning and induces last-minute changes resulting in additional costs. Developing vehicle routing models incorporating loading constraints is critical to more efficient route planning. The last couple of years has seen a huge increase of contributions to this field of research with almost 60 % of these being published after 2009. Our contribution is twofold. First, we overview the recent developments in the literature on all vehicle types in which loading constraints play a key role (trucks, airplanes, ships, and automated guided vehicles), using a state-of-the-art classification scheme to identify the loading constraints considered in each article. Second, we identify research gaps and opportunities for future research.

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Section: Traveling Salesman Problem With Pickups and Deliveries With mentioning

confidence: 98%

Section: Traveling Salesman Problem With Pickups and Deliveries With mentioning

confidence: 99%

Vehicle routing problems with loading constraints: state-of-the-art and future directions

et al. 2014

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“…Finally, we show how these inequalities were extended by Côté et al. () to cope with the more general case in which the vehicle contains more than one stack of finite capacity.…”

Section: Mathematical Modelsmentioning

confidence: 99%

“…We use problem instances from the literature to evaluate our B&C algorithm, and the results show that our approach is competitive with the B&C algorithm in Côté et al. (). Also, three new certificates of optimality are provided and several optimality gaps are reduced.…”

Section: Introductionmentioning

confidence: 98%

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New formulation and branch‐and‐cut algorithm for the pickup and delivery traveling salesman problem with multiple stacks

Sampaio

Urrutia

2016

Int Trans Operational Res

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In this paper, we consider the pickup and delivery traveling salesman problem with multiple stacks in which a single vehicle must serve a set of customer requests defined by a pair of pickup and delivery destinations of an item. The vehicle contains a fixed number of stacks, where each item is loaded at a pickup location and unloaded at the corresponding delivery location. Each stack has finite capacity, and its loading and unloading sequence must follow the last-in-first-out (LIFO) policy, that is, for each stack, just the last item loaded can be unloaded at its corresponding delivery location. We propose a new integer programming formulation for this problem with a polyhedral representation described by exponentially many inequalities and a branch-and-cut algorithm for solving the proposed formulation. Computational results show that our approach is competitive with the best algorithm in the literature. Also, three new certificates of optimality are provided and several optimality gaps are reduced.

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Iterated local search for the capacitated vehicle routing problem with sequence‐based pallet loading and axle weight constraints

et al. 2017

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In this article an Iterated Local Search algorithm for the capacitated vehicle routing problem with sequencebased pallet loading and axle weight constraints is presented. Axle weight limits impose a great challenge for transportation companies. Yet, the literature on the incorporation of axle weight constraints in vehicle routing models is very scarce. The effect of introducing axle weight constraints in a CVRP on total routing cost is analyzed. Results show that integrating axle weight constraints does not lead to a large cost increase. However, not including axle weight constraints in the planning process may induce major axle weight violations.

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A branch‐and‐cut algorithm for the pickup and delivery traveling salesman problem with multiple stacks

Cited by 27 publications

References 33 publications

Vehicle routing problems with loading constraints: state-of-the-art and future directions

Vehicle routing problems with loading constraints: state-of-the-art and future directions

New formulation and branch‐and‐cut algorithm for the pickup and delivery traveling salesman problem with multiple stacks

Iterated local search for the capacitated vehicle routing problem with sequence‐based pallet loading and axle weight constraints

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