Multiobjective routing problems

Boffey, Brian; García, Francisco Ramón Fernández; Laporte, Gilbert; Mesa, Juan A.; Pelegrı́n, Blas

doi:10.1007/bf02568585

Cited by 23 publications

(15 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, there are several multi-objective routing approaches that focus on so-called Multi-Objective Routing Problems (MORPs) [5]. In [2], [7], and [14], Evolutionary Algorithms are used to search for Pareto-optimal multi-cast routings for a given topology.…”

Section: Related Workmentioning

confidence: 99%

Multi-objective routing and topology optimization in networked embedded systems

Glaß

Lukasiewycz

Wanka

et al. 2008

2008 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation

View full text Add to dashboard Cite

Abstract-Modern networked embedded system design has to cope with multiple design objectives. One major challenge is the determination of optimal routings with respect to these objectives. Existing automatic optimization approaches carry out a two step optimization: First, they perform a multi-objective topology optimization of the networked embedded system. Then, a multi-objective routing optimization for a subset of Paretooptimal solutions obtained from the first step is performed. In general, this may exclude several globally optimal solutions from the optimization process. To overcome this drawback, a unified approach based on Multi-Objective Evolutionary Algorithms is presented that ensures a combined optimization of the topology and routing. Since the system topology is varied within the optimization, the main contribution of this paper contribution is a novel routing technique that always samples feasible paths using a topology independent genetic encoding. This encoding preserves optimized routing information when changing the underlying topology. An experimental evaluation shows the effectiveness of the presented approach.

show abstract

Section: Related Workmentioning

confidence: 99%

Multi-objective routing and topology optimization in networked embedded systems

Glaß

Lukasiewycz

Wanka

et al. 2008

2008 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation

View full text Add to dashboard Cite

show abstract

“…On the basis of the procedure introduced by Rosen et al, Boffey et al (2002) applied a method already used by Boffey (1996) for minsum-maxmin problems. Its application sets out to take advantage of the similarity between two successive Rosen et al networks.…”

Section: Boffey Et Al's Algorithmmentioning

confidence: 99%

A comprehensive survey on the quickest path problem

2006

View full text Add to dashboard Cite

This work is a survey on a special minsum-maxmin bicriteria problem, known as the quickest path problem, that can model the transmission of data between two nodes of a network. Moreover, the authors review the problems of ranking the K quickest paths, and the K quickest loopless paths, and compare them in terms of the worst-case complexity order. The classification presented led to the proposal of a new variant of a known K quickest loopless paths algorithm. Finally, applications of quickest path algorithms are mentioned, as well as some comparative empirical results. Keywords Bicriteria problem . Minsum-maxmin . Quickest path . Paths rankingThe quickest path problem is a particular case of optimal path problems, whose objective function evaluates the time taken to transmit a given amount of data through each path. This function depends on two parameters, an additive function that represents the path delay, and a bottleneck function that represents the path capacity or bandwidth. Thus, the resolution of

show abstract

“…For further investigation on routing problems, readers are referred to the following works: the state of the art on exact and approximated methods for the VRP and its variants are found in [14] and an overview covering about 500 papers on classical routing problems are found in [9]. For multiobjective solutions strategies on routing problems, see [3,7].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Mobile Oil Recovery Problem as a Multiobjective Vehicle Routing Problem

Santos

Duhamel

Aloise

2008

Communications in Computer and Information Science

View full text Add to dashboard Cite

Abstract. The Mobile Oil Recovery (MOR) unit is a truck able to pump marginal wells in a petrol field. The goal of the MOR optimization Problem (MORP) is to optimize both the oil extraction and the travel costs. We describe several formulations for the MORP using a single vehicle or a fleet of vehicles. We have also strengthened them by improving the subtour elimination constraints. Optimality is proved for instances close to reality with up to 200 nodes.

show abstract

Multiobjective routing problems

Abstract: Hazardous materials, Efficient Solutions, k-Shortest Path Methods,

Cited by 23 publications

References 46 publications

Multi-objective routing and topology optimization in networked embedded systems

Multi-objective routing and topology optimization in networked embedded systems

A comprehensive survey on the quickest path problem

Modeling the Mobile Oil Recovery Problem as a Multiobjective Vehicle Routing Problem

Contact Info

Product

Resources

About