Multi-objective vehicle routing problems

Jozefowiez, Nicolas; Semet, Frédéric; Talbi, El‐Ghazali

doi:10.1016/j.ejor.2007.05.055

Cited by 393 publications

(194 citation statements)

References 59 publications

(135 reference statements)

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“…But what does lowest-cost mean? Since the problem was proposed by Dantzig and Ramser [2] as a generalization of the Traveling Salesman Problem, cost has mostly been associated with the travel distance, but there are several other types of cost involved, such as the number of vehicles and delivery time [3]. The VRP also has several variants that involve different constraints.…”

Section: Introductionmentioning

confidence: 99%

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

García-Nájera

Bullinaria

2011

Computers & Operations Research

154

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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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Section: Introductionmentioning

confidence: 99%

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

García-Nájera

Bullinaria

2011

Computers & Operations Research

154

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“…Given the promising performance of our algorithm, we are now looking at the possibility of optimizing even more objectives (such as route balance [1]), and pursuing the comparison of our results with other multi-criterion optimization methods and further multi-objective performance metrics.…”

Section: Discussionmentioning

confidence: 99%

“…Its objective is to obtain the lowest-cost set of routes to deliver demand to customers. Since the problem was originally formulated as a generalization of the Traveling Salesman Problem, cost has primarily been associated with the number of routes and travel distance, but there are several other types of cost [1].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Delivery Time in Multi-Objective Vehicle Routing Problems with Time Windows

García-Nájera

Bullinaria

2010

Parallel Problem Solving From Nature, PPSN XI

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Abstract. The Vehicle Routing Problem with Time Windows involves finding the lowest-cost set of routes to deliver goods to customers, which have service time windows, using a homogeneous fleet of vehicles with limited capacity. In this paper, we propose and analyze the performance of an improved multi-objective evolutionary algorithm, that simultaneously minimizes the number of routes, the total travel distance, and the delivery time. Empirical results indicate that the simultaneous minimization of all three objectives leads the algorithm to find similar or better results than any combination of only two objectives. These results, although not the best in all respects, are better in some aspects than all previously published approaches, and fully multi-objective comparisons show clear improvement over the popular NSGA-II algorithm.

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“…For a detailed review of multi-objective problems, see Jozefowiez et al [2]. Excellent references for the Traveling Salesman Problem (TSP), the Vehicle Routing Problem (VRP), and arc routing problems are by Gutin [3], Applegate et al [4], Golden et al [5], Dror [6], and Braekers et al [7].…”

Section: Literature Reviewmentioning

confidence: 99%

A Bi-Modal Routing Problem with Cyclical and One-Way Trips: Formulation and Heuristic Solution

Grinde

2017

Information Technology and Management Science

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-A bi-modal routing problem is solved using a heuristic approach. Motivated by a recreational hiking application, the problem is similar to routing problems in business with two transport modes. The problem decomposes into a set covering problem (SCP) and an asymmetric traveling salesperson problem (ATSP), corresponding to a hiking time objective and a driving distance objective. The solution algorithm considers hiking time first, but finds all alternate optimal solutions, as inputs to the driving distance problem. Results show the trade-offs between the two objectives.

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Multi-objective vehicle routing problems

Cited by 393 publications

References 59 publications

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

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

Optimizing Delivery Time in Multi-Objective Vehicle Routing Problems with Time Windows

A Bi-Modal Routing Problem with Cyclical and One-Way Trips: Formulation and Heuristic Solution

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