Multi-objective Vehicle Routing Problems Using Two-Fold EMO Algorithms to Enhance Solution Similarity on Non-dominated Solutions

Murata, Tadahiko; Itai, Ryota

doi:10.1007/978-3-540-31880-4_61

Cited by 28 publications

(18 citation statements)

References 7 publications

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“…For example, Murata and Itai [9] applied this algorithm on a VRP with two different types of demands. They focused the study on the optimisation of number of vehicles and makespan considering the similarity of sets of non-dominated solutions.…”

Section: Non-dominated Sorting Genetic Algorithm (Nsga-ii)mentioning

confidence: 99%

Nature of real-world multi-objective vehicle routing with evolutionary algorithms

Castro-Gutierrez

Landa-Silva

Perez

2011

2011 IEEE International Conference on Systems, Man, and Cybernetics

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract-The Vehicle Routing Problem with Time Windows (VRPTW) is an important logistics problem which in the realworld appears to be multi-objective. Most research in this area has been carried out using classic datasets designed for the single-objective case, like the well-known Solomon's problem instances. Some unrealistic assumptions are usually made when using these datasets in the multi-objective case (e.g. assuming that one unit of travel time corresponds to one unit of travel distance). Additionally, there is no common VRPTW multiobjective oriented framework to compare the performance of algorithms because different implementations in the literature tackle different sets of objectives. In this work, we investigate the conflicting (or not) nature of various objectives in the VRPTW and show that some of the classic test instances are not suitable for conducting a proper multi-objective study. The insights of this study have led us to generate some problem instances using data from a real-world distribution company. Experiments in these new dataset using a standard evolutionary algorithm (NSGA-II) show stronger evidence of multi-objective features. Our contribution focuses on achieving a better understanding about the multi-objective nature of the VRPTW, in particular the conflicting relationships between 5 objectives: number of vehicles, total travel distance, makespan, total waiting time, and total delay time.

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Section: Non-dominated Sorting Genetic Algorithm (Nsga-ii)mentioning

confidence: 99%

Nature of real-world multi-objective vehicle routing with evolutionary algorithms

Castro-Gutierrez

Landa-Silva

Perez

2011

2011 IEEE International Conference on Systems, Man, and Cybernetics

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“…Murata and Itai [26] proposed a two-fold evolutionary multi-objective algorithm for solving a variant of the VRP in which customers have normal and high demands. They also proposed a similarity measure to show the importance of examining characteristics of solutions to both problems.…”

Section: Previous Studiesmentioning

confidence: 99%

An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows

García-Nájera

Bullinaria

2011

Computers & Operations Research

158

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The Vehicle Routing Problem with Time Windows is a complex combinatorial problem with many real-world applications in transportation and distribution logistics. Its main objective is to find the lowest distance set of routes to deliver goods, using a fleet of identical vehicles with restricted capacity, to customers with service time windows. However, there are other objectives, and having a range of solutions representing the trade-offs between objectives is crucial for many applications. Although previous research has used evolutionary methods for solving this problem, it has rarely concentrated on the optimization of more than one objective, and hardly ever explicitly considered the diversity of solutions. This paper proposes and analyzes a novel multi-objective evolutionary algorithm, which incorporates methods for measuring the similarity of solutions, to solve the multi-objective problem. The algorithm is applied to a standard benchmark problem set, showing that when the similarity measure is used appropriately, the diversity and quality of solutions is higher than when it is not used, and the algorithm achieves highly competitive results compared with previously published studies and those from a popular evolutionary multi-objective optimizer.

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“…The second is known as the multi-depot problem that tries to deliver from multiple depots (Chen et al, 2005;Crevier et al, 2007;Wu et al, 2002). The thirds are interested in the multi-objective formulation for the single depot and multidepot problems (Bou and Arakawa, 2010;Geiger, 2010;Jozefowiez et al, 2008;Murata and Itai, 2005;Pasia et al, 2007;Tan et al, 2006). The decision on the locations of depot is involved besides VRP in the last one (AlbaredaSambola et al, 2005;Prins et al, 2006;Tuzun and Burke, 1999;Zhao et al, 2008).…”

Section: Brief Reviewmentioning

confidence: 99%

Generalized Vehicle Routing Problem for Reverse Logistics Aiming at Low Carbon Transportation

Shimizu

Sakaguchi²

2013

Industrial Engineering and Management Systems

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Deployment of green transportation in reverse logistics is a key issue for low carbon technologies. To cope with such logistic innovation, this paper proposes a hybrid approach to solve practical vehicle routing problem (VRP) of pickup type that is common when considering the reverse logistics. Noticing that transportation cost depends not only on distance traveled but also on weight loaded, we propose a hierarchical procedure that can design an economically efficient reverse logistics network even when the scale of the problem becomes very large. Since environmental concerns are of growing importance in the reverse logistics field, we need to reveal some prospects that can reduce CO 2 emissions from the economically optimized VRP in the same framework. In order to cope with manifold circumstances, the above idea has been deployed by extending the Weber model to the generalized Weber model and to the case with an intermediate destination. Numerical experiments are carried out to validate the effectiveness of the proposed approach and to explore the prospects for future green reverse logistics.

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Multi-objective Vehicle Routing Problems Using Two-Fold EMO Algorithms to Enhance Solution Similarity on Non-dominated Solutions

Cited by 28 publications

References 7 publications

Nature of real-world multi-objective vehicle routing with evolutionary algorithms

Nature of real-world multi-objective vehicle routing with evolutionary algorithms

An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows

Generalized Vehicle Routing Problem for Reverse Logistics Aiming at Low Carbon Transportation

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