1,030 research outputs found
Workload Equity in Vehicle Routing Problems: A Survey and Analysis
Over the past two decades, equity aspects have been considered in a growing
number of models and methods for vehicle routing problems (VRPs). Equity
concerns most often relate to fairly allocating workloads and to balancing the
utilization of resources, and many practical applications have been reported in
the literature. However, there has been only limited discussion about how
workload equity should be modeled in VRPs, and various measures for optimizing
such objectives have been proposed and implemented without a critical
evaluation of their respective merits and consequences.
This article addresses this gap with an analysis of classical and alternative
equity functions for biobjective VRP models. In our survey, we review and
categorize the existing literature on equitable VRPs. In the analysis, we
identify a set of axiomatic properties that an ideal equity measure should
satisfy, collect six common measures, and point out important connections
between their properties and those of the resulting Pareto-optimal solutions.
To gauge the extent of these implications, we also conduct a numerical study on
small biobjective VRP instances solvable to optimality. Our study reveals two
undesirable consequences when optimizing equity with nonmonotonic functions:
Pareto-optimal solutions can consist of non-TSP-optimal tours, and even if all
tours are TSP optimal, Pareto-optimal solutions can be workload inconsistent,
i.e. composed of tours whose workloads are all equal to or longer than those of
other Pareto-optimal solutions. We show that the extent of these phenomena
should not be underestimated. The results of our biobjective analysis are valid
also for weighted sum, constraint-based, or single-objective models. Based on
this analysis, we conclude that monotonic equity functions are more appropriate
for certain types of VRP models, and suggest promising avenues for further
research.Comment: Accepted Manuscrip
A New Model for The Multi-Objective Multiple Allocation Hub Network Design and Routing Problem
In this paper, we propose a new model for the multi-objective multiple allocation hub network
design and routing problem which contains determining the location of hubs, the design of hub network, and
the routing of commodities between source-destination pairs in the given network. The selected hubs are not
assumed to be fully connected, and each node and arc in the network has capacity constraints. The multiple
objectives of the problem are the minimization of total xed and transportation costs and the minimization
of the maximum travel time required for routing. We propose a mathematical formulation for the multiobjective
problem and present a meta-heuristic solution based on a well-known multi-objective evolutionary
algorithm. Using the proposed formulation, we are able to nd the optimal solution for small networks of ve
nodes and seven nodes. To evaluate the performance of our heuristic approach on real data, the computational
experiments are conducted on Turkish postal system data set. The results demonstrate that our heuristic
approach can nd feasible solutions to the problem in reasonable execution time, which is less than 10 min
Arc routing problems: A review of the past, present, and future
[EN] Arc routing problems (ARPs) are defined and introduced. Following a brief history of developments in this area of research, different types of ARPs are described that are currently relevant for study. In addition, particular features of ARPs that are important from a theoretical or practical point of view are discussed. A section on applications describes some of the changes that have occurred from early applications of ARP models to the present day and points the way to emerging topics for study. A final section provides information on libraries and instance repositories for ARPs. The review concludes with some perspectives on future research developments and opportunities for emerging applicationsThis research was supported by the Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional, Grant/Award Number: PGC2018-099428-B-I00. The Research Council of Norway, Grant/Award Numbers: 246825/O70 (DynamITe), 263031/O70 (AXIOM).Corberán, Á.; Eglese, R.; Hasle, G.; Plana, I.; Sanchís Llopis, JM. (2021). Arc routing problems: A review of the past, present, and future. Networks. 77(1):88-115. https://doi.org/10.1002/net.21965S8811577
A bi-objective stochastic approach for stochastic CARP
The Capacitated Arc Routing Problem (CARP) occurs in applications like urban waste collection or winter gritting. It is usually defined in literature on an undirected graph G = (V, E) , with a set V of n nodes and a set E of m edges. A fleet of identical vehicles of capacity Q is based at a depot node. Each edge i has a cost (length) ci and a demand qi (e.g. an amount of waste), and it may be traversed any number of times. The edges with non-zero demands or tasks require service by a vehicle. The goal is to determine a set of vehicle trips (routes) of minimum total cost, such that each trip starts and ends at the depot, each task is serviced by one single trip, and the total demand handled by any vehicle does not exceed Q . To the best of our knowledge the best published method is a memetic algorithm first introduced in 2001. This article provides a new extension of the NSGA II (Non-dominated Sorting Genetic Algorithm) template to comply with the stochastic sight of the CARP. The main contribution is: - to introduce mathematical expression to evaluate both cost and duration of the longest trip and also standard deviation of these two criteria. - to use a NGA-II template to optimize simultaneously the cost and the duration of the longest trip including standard deviation. The numerical experiments managed on the thee well-known benchmark sets of DeArmon, Belenguer and Benavent and Eglese, prove it is possible to obtain robust solutions in four simultaneous criteria in rather short computation times
Experimental Evaluation of Meta-Heuristics for Multi-Objective Capacitated Multiple Allocation Hub Location Problem
Multi-objective capacitated multiple allocation hub location problem (MOCMAHLP) is a variation of classic
hub location problem, which deals with network design, considering both the number and the location
of the hubs and the connections between hubs and spokes, as well as routing of flow on the network.
In this study, we offer two meta-heuristic approaches based on the non-dominated sorting genetic algorithm
(NSGA-II) and archived multi-objective simulated annealing method (AMOSA) to solve
MOCMAHLP. We attuned AMOSA based approach to obtain feasible solutions for the problem and developed
five different neighborhood operators in this approach. Moreover, for NSGA-II based approach, we
developed two novel problem-specific mutation operators. To statistically analyze the behavior of both
algorithms, we conducted experiments on two well-known data sets, namely Turkish and Australian
Post (AP). Hypervolume indicator is used as the performance metric to measure the effectiveness of both
approaches on the given data sets. In the experimental study, thorough tests are conducted to fine-tune
the proposed mutation types for NSGA-II and proposed neighborhood operators for AMOSA. Fine-tuning
tests reveal that for NSGA-II, mutation probability does not have a real effect on Turkish data set, whereas
lower mutation probabilities are slightly better for AP data set. Moreover, among the AMOSA based
neighborhood operators, the one which adds/removes a specific number of links according to temperature
(NS-5) performs better than the others for both data sets. After analyzing different operators for both
algorithms, a comparison between our NSGA-II based and AMOSA based approaches is performed with
the best settings. As a result, we conclude that both of our algorithms are able to find feasible solutions
of the problem. Moreover, NSGA-II performs better for larger, whereas AMOSA performs better for smaller
size networks
REVISIÓN DE LA LITERATURA DEL PROBLEMA DE RUTEO DE VEHÍCULOS EN UN CONTEXTO DE TRANSPORTE VERDE
In the efficient management of the supply chain the optimal management of transport of consumables and finished products appears. The costs associated with transport have direct impact on the final value consumers must pay, which in addition to requiring competitive products also demand that they are generated in environmentally friendly organizations. Aware of this reality, this document is intended to be a starting point for Master's and Doctoral degree students who want to work in a line of research recently proposed: green routing. The state of the art of the vehicle routing problem is presented in this paper, listing its variants, models and methodologies for solution. Furthermore, the proposed interaction between variants of classical routing problems and environmental effects of its operations, known in the literature as Green-VRP is presented. The goal is to generate a discussion in which mathematical models and solution strategies that can be applied within organizations that consider within their objectives an efficient and sustainable operation are posed. En el gerenciamiento eficiente de la cadena de suministro aparece la gestión óptima del transporte de insumos y productos terminados. Los costos asociados al transporte tienen impacto directo sobre el valor final que deben pagar los consumidores, que además de requerir productos competitivos también exigen que los mismos sean generados en organizaciones amigables con el medioambiente. Consientes de esa realidad este documento pretende ser un punto de partida para estudiantes de maestría y doctorado que quieran trabajar en una línea de investigación propuesta recientemente: el ruteo verde. En este trabajo se muestra un estado del arte del problema de ruteo de vehículos, enumerando sus variantes, modelos y metodologías de solución. Además, se presenta la interacción que se ha propuesto entre variantes clásicas de los problemas de ruteo y los efectos ambientales de su operación, denominados en la literatura como Green-VRP. El objetivo es generar una discusión donde se planteen modelos matemáticos y estrategias de solución que puedan ser aplicadas en organizaciones que consideren dentro de sus objetivos una operación eficiente y sustentable.
Document type: Articl
Revisión de la literatura del problema de ruteo de vehículos en un contexto de transporte verde
In the efficient management of the supply chain the optimal management of transport of consumables and finished products appears. The costs associated with transport have direct impact on the final value consumers must pay, which in addition to requiring competitive products also demand that they are generated in environmentally friendly organizations. Aware of this reality, this document is intended to be a starting point for Master’s and Doctoral degree students who want to work in a line of research recently proposed: green routing. The state of the art of the vehicle routing problem is presented in this paper, listing its variants, models and methodologies for solution. Furthermore, the proposed interaction between variants of classical routing problems and environmental effects of its operations, known in the literature as Green- VRP is presented. The goal is to generate a discussion in which mathematical models and solution strategies that can be applied within organizations that consider within their objectives an efficient and sustainable operation are posed.En el gerenciamiento eficiente de la cadena de suministro aparece la gestión óptima del transporte de insumos y productos terminados. Los costos asociados al transporte tienen impacto directo sobre el valor final que deben pagar los consumidores, que además de requerir productos competitivos también exigen que los mismos sean generados en organizaciones amigables con el medioambiente. Consientes de esa realidad este documento pretende ser un punto de partida para estudiantes de maestría y doctorado que quieran trabajar en una línea de investigación propuesta recientemente: el ruteo verde. En este trabajo se muestra un estado del arte del problema de ruteo de vehículos, enumerando sus variantes, modelos y metodologías de solución. Además, se presenta la interacción que se ha propuesto entre variantes clásicas de los problemas de ruteo y los efectos ambientales de su operación, denominados en la literatura como Green-VRP. El objetivo es generar una discusión donde se planteen modelos matemáticos y estrategias de solución que puedan ser aplicadas en organizaciones que consideren dentro de sus objetivos una operación eficiente y sustentable
The Vehicle Routing Problem with Service Level Constraints
We consider a vehicle routing problem which seeks to minimize cost subject to
service level constraints on several groups of deliveries. This problem
captures some essential challenges faced by a logistics provider which operates
transportation services for a limited number of partners and should respect
contractual obligations on service levels. The problem also generalizes several
important classes of vehicle routing problems with profits. To solve it, we
propose a compact mathematical formulation, a branch-and-price algorithm, and a
hybrid genetic algorithm with population management, which relies on
problem-tailored solution representation, crossover and local search operators,
as well as an adaptive penalization mechanism establishing a good balance
between service levels and costs. Our computational experiments show that the
proposed heuristic returns very high-quality solutions for this difficult
problem, matches all optimal solutions found for small and medium-scale
benchmark instances, and improves upon existing algorithms for two important
special cases: the vehicle routing problem with private fleet and common
carrier, and the capacitated profitable tour problem. The branch-and-price
algorithm also produces new optimal solutions for all three problems
A hybrid algorithm combining path scanning and biased random sampling for the Arc Routing Problem
The Arc Routing Problem is a kind of NP-hard routing problems
where the demand is located in some of the arcs connecting nodes
and should be completely served fulfilling certain constraints. This paper
presents a hybrid algorithm which combines a classical heuristic with biased
random sampling, to solve the Capacitated Arc Routing Problem
(CARP). This new algorithm is compared with the classical Path scanning
heuristic, reaching results which outperform it. As discussed in the
paper, the methodology presented is flexible, can be easily parallelised
and it does not require any complex fine-tuning process. Some preliminary
tests show the potential of the proposed approach as well as its
limitationsPostprint (published version
- …