A Heuristic for the Periodic Vehicle Routing Problem

Gaudioso, Manlio; Paletta, Giuseppe

doi:10.1287/trsc.26.2.86

Cited by 106 publications

(60 citation statements)

References 6 publications

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“…Although IRPs have appeared in the literature as early as in the 1970s (e.g., Beltrami andBodin, 1974 andRussell andIgo, 1979), much of the research is more recent (e.g., Anily and Federgruen, 1990and 1993, Bell et al, 1983, Bard et al, 1998, Berman and Larson, 1999, Chan, Federgruen, and Simchi-Levi, 1998, Chan, Muriel, and Simchi-Levi, 1998, Chien, Balakrishnan, and Wong, 1989, Christofides and Beasley, 1984, Dror and Ball, 1987, Dror, Ball, and Golden, 1985, Federgruen and Simchi-Levi, 1995, Federgruen and Zipkin, 1984, Gaudioso and Paletta, 1992, Golden, Assad, and Dahl, 1984, Kleywegt, Nori, and Savelsbergh, 1998and 2000, Kumar, Schwarz, and Ward, 1995, Reiman, Rubio, and Wein, 1999, Rubio, 1995, Trudeau and Dror, 1992, and Webb and Larson, 1995.…”

Section: Introductionmentioning

confidence: 99%

Delivery Cost Approximations for Inventory Routing Problems in a Rolling Horizon Framework

Jaillet

Bard

Huang³

et al. 2002

Transportation Science

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The inventory routing problem considered in this paper is concerned with the repeated distribution of a commodity, such as heating oil, over a long period of time to a large number of customers. The problem involves a central depot as well as various satellite facilities which the drivers can visit during their shift to refill their vehicles. The customers maintain a local inventory of the commodity.Their consumption varies daily and cannot be predicted deterministically. In case of a stockout, a direct delivery is made and a penalty cost is incurred. In this paper we present incremental cost approximations to be used in a rolling horizon framework for the problem of minimizing the total expected annual delivery costs.

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Section: Introductionmentioning

confidence: 99%

Delivery Cost Approximations for Inventory Routing Problems in a Rolling Horizon Framework

Jaillet

Bard

Huang³

et al. 2002

Transportation Science

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“…Mourgaya and Vanderbeck (2007) presented a column generation procedure followed by a rounding heuristic to solve a PVRP with two objectives: minimizing total distance travelled and balance workload among vehicles. Other heuristic applications to PVRP can be found in Christofides and Beasley (1984), Gaudioso and Paletta (1992), Chao et al (1995), Cordeau et al (1997) and Alonso et al (2008), to name a few.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing and improving management practices when planning packaging waste collection systems

Ramos

Gomes

Barbosa‐Póvoa

2014

Resources, Conservation and Recycling

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a b s t r a c tPackaging waste collection systems are responsible to collect, within a geographic area, three types of packaging materials (paper, glass and plastic/metal) that are disposed by the final consumer into special bins. Those systems are often characterized by having a network with multiple depots that act as transfer and sorting stations, and where the vehicle fleet is based. However, each depot is often managed independently and not as a part of a unique system. In this work, four current tactical/operational practices that contribute to the independent management of each depot are analysed. The change of such practices is investigated and their impact assessed on the total collection cost. A solution methodology based on mathematical formulations is developed to plan service areas, vehicle routes and vehicle schedules taking into account new alternative solutions in managing the system as a whole. Such methodology is applied to a real case study of a company responsible for the collection of the packaging waste in 7 municipalities in mainland Portugal. New service areas, collection routes and vehicle schedules are defined and significant savings are obtained in terms of the total distance travelled as well as in terms of the number of required vehicles, resulting in a decreasing of the total system cost.

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“…These approaches, as described in Christofides and Beasley (1984) and Gaudioso and Paletta (1992), are better for making strategic decisions such as determining fleet size rather than short-term planning. The true stochastic nature of the problem makes these approaches unsuccessful and inefficient in the short term.…”

Section: Related Workmentioning

confidence: 99%

A Decomposition Approach for the Inventory-Routing Problem

Campbell

Savelsbergh

2004

Transportation Science

248

104

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I n this paper, we present a solution approach for the inventory-routing problem. The inventory-routing problem is a variation of the vehicle-routing problem that arises in situations where a vendor has the ability to make decisions about the timing and sizing of deliveries, as well as the routing, with the restriction that customers are not allowed to run out of product. We develop a two-phase approach based on decomposing the set of decisions: A delivery schedule is created first, followed by the construction of a set of delivery routes. The first phase utilizes integer programming, whereas the second phase employs routing and scheduling heuristics. Our focus is on creating a solution methodology appropriate for large-scale real-life instances. Computational experiments demonstrating the effectiveness of our approach are presented.

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A Heuristic for the Periodic Vehicle Routing Problem

Cited by 106 publications

References 6 publications

Delivery Cost Approximations for Inventory Routing Problems in a Rolling Horizon Framework

Delivery Cost Approximations for Inventory Routing Problems in a Rolling Horizon Framework

Assessing and improving management practices when planning packaging waste collection systems

A Decomposition Approach for the Inventory-Routing Problem

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