Optimizing vehicle routes in a bakery company allowing flexibility in delivery dates

Pacheco, Joaquín; Alvarez, Ada M.; García, Irma; Ángel-Bello, Francisco

doi:10.1057/jors.2011.51

Cited by 21 publications

(17 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the old PVRP test set, the authors achieve a performance that comes close to that of the hybrid Genetic Algorithm (GA) of Vidal et al [144]; however, their algorithm requires clearly higher run times. On the realistic instances of Pacheco et al [107] (see below), their matheuristic is able to obtain better solution quality than the approaches presented in Alegre, Laguna, and Pacheco [1], Cordeau, Gendreau, and Laporte [45], Hemmelmayr, Doerner, and Hartl [76], and Pacheco et al [107], again requiring significantly higher computational effort.…”

Section: Exact Methods and Matheuristicsmentioning

confidence: 95%

“…Pacheco et al [107] address a variant of the PVRP faced by a Spanish bakery company planning its deliveries to distribution centers, in which delivery to a customer has to take place within a certain time before a deadline associated with the customer. To decide the delivery day for each customer and construct the daily routes, the authors propose a twophase algorithm, consisting of a GRASP phase with local improvement to generate a set of high-quality and diverse solutions and a PR phase to intensify the search.…”

Section: Case Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Chapter 9: Four Variants of the Vehicle Routing Problem

Irnich¹,

Schneider²,

Vigo³

2014

Vehicle Routing

View full text Add to dashboard Cite

In this chapter, we review four important variants of the Vehicle Routing Problem (VRP): 1. VRP with Backhauls (VRPB); 2. Heterogeneous or mixed Fleet VRP (HFVRP); 3. Periodic VRP (PVRP); 4. Split Delivery VRP (SDVRP).Each family plays an important role in the literature and considers a characteristic feature often encountered, both alone and combined, in real-world applications. The resulting VRP variants are non-trivial extensions of the basic VRP, and they all deserve specifically tailored algorithmic approaches for their effective solution.In the first problem class, the VRP with Backhauls (VRPB), the customers are partitioned into two sets, the linehaul and backhaul customers. The linehaul customers require the delivery of goods from the depot, and the backhaul customers have goods to be picked up and transported to the depot. Since a rearrangement of the load inside a vehicle is often impossible or undesirable, e.g., because the vehicle's loading space is only accessible from the rear, a precedence relation on the service of linehaul and backhaul customers is imposed: In a feasible VRPB solution the combined service of linehauls and backhauls in the same route is possible, but all linehaul customers receive their demand before load at backhaul customers is picked up. The VRPB belongs to the more general class of delivery and collection VRP, which clearly introduces considerable improvements over separate distribution and collection services in different routes.In the second variant, the family of Heterogeneous or mixed Fleet VRP (HFVRP), the fleet consists of different vehicles or vehicle types, each with a specific capacity and costs.

show abstract

Section: Exact Methods and Matheuristicsmentioning

confidence: 95%

Section: Case Studiesmentioning

confidence: 99%

Chapter 9: Four Variants of the Vehicle Routing Problem

Irnich¹,

Schneider²,

Vigo³

2014

Vehicle Routing

View full text Add to dashboard Cite

show abstract

“…In Pacheco et al. (), the authors propose a mixed‐integer linear model for an MPVRP based on a real‐life case. Also, a greedy randomized adaptive search procedure (also known as GRASP) with path‐relinking metaheuristic is proposed to solve the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Biased‐randomized iterated local search for a multiperiod vehicle routing problem with price discounts for delivery flexibility

Estrada‐Moreno

Juan

Panadero

2019

Int Trans Operational Res

View full text Add to dashboard Cite

The multiperiod vehicle routing problem (MPVRP) is an extension of the vehicle routing problem in which customer demands have to be delivered in one of several consecutive time periods, for example, the days of a week. We introduce and explore a variant of the MPVRP in which the carrier offers a price discount in exchange for delivery flexibility. The carrier's goal is to minimize total costs, which consist of the distribution costs and the discounts paid. A biased-randomized iterated local search algorithm is proposed for its solution. The two-stage algorithm first quickly generates a number of promising customer-to-period assignments, and then intensively explores a subset of these assignments. An extensive computational study demonstrates the efficacy of the proposed algorithm and highlights the benefit of pricing for delivery flexibility in different settings.

show abstract

“…Pirkwieser and Raidl (2010) introduce an extension of VNS metaheuristics with multilevel refinement strategy particularly suitable for larger PVRP instances. A two-phase GRASP and path relinking metaheuristic is proposed by Pacheco et al (2012). A significant contribution is given by Vidal et al (2012) that propose a hybrid genetic algorithm to tackle the MDPVRP and PVRP with heterogeneous capacitated vehicles and constrained route duration.…”

Section: Literature Reviewmentioning

confidence: 99%

Periodic Capacitated Vehicle Routing for Retail Distribution of Fuel Oils

Carotenuto

Giordani

Massari

et al. 2015

Transportation Research Procedia

View full text Add to dashboard Cite

In this paper we consider the final distribution of fuel oil from a storage depot to a set of petrol stations faced by an oil company, which has to decide the weekly replenishment plan for each station, and determine petrol station visiting sequences (vehicle routes) for each day of the week, assuming a fleet of homogeneous vehicles (tankers). The aim is to minimize the total distance travelled by tankers during the week, while loading tankers possibly near to their capacity in order to maximize the resource utilization. The problem is modelled as a generalization of the Periodic Vehicle Routing Problem (PVRP). Due to the large size of the real instances which the company has to deal with, we solve the problem heuristically. We propose a hybrid genetic algorithm that successfully address the problem inspired to a known hybrid genetic algorithm from the literature for the PVRP. However, the proposed algorithm adopts some techniques and features tailored for the particular fuel oil distribution problem, and it is specifically designed to deal with real instances derived from the fuel oil distribution in the European context that are profoundly different from the PVRP instances available from literature. The proposed algorithm is evaluated on a set of real case studies and on a set of randomly generated instances that hold the same characteristics of the former.

show abstract

Optimizing vehicle routes in a bakery company allowing flexibility in delivery dates

Cited by 21 publications

References 46 publications

Chapter 9: Four Variants of the Vehicle Routing Problem

Chapter 9: Four Variants of the Vehicle Routing Problem

Biased‐randomized iterated local search for a multiperiod vehicle routing problem with price discounts for delivery flexibility

Periodic Capacitated Vehicle Routing for Retail Distribution of Fuel Oils

Contact Info

Product

Resources

About