README.md

dynvrp

This repository contains the implementation of a dynamic evolutionary multi-objective algorithm for a bi-objective orienteering where the goal is to minimize the length of the tour traveled by a single vehicle and maximize the number of dynamic customer requests which arrive as time passes by.

Previous work

In previous work we developed and studied an a posteriori version of the EMOA where all dynamic requests were known in advance.

Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, and Heike Trautmann. Local Search Effects in Bi-objective Orienteering. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO ’18, pages 585-592, New York, NY, USA, 2018. ACM.

Stephan Meisel, Christian Grimme, Jakob Bossek, Martin Wölck, Günter Rudolph, and Heike Trautmann. Evaluation of a Multi-Objective EA on Benchmark In- stances for Dynamic Routing of a Vehicle. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, GECCO ’15, pages 425-432, New York, NY, USA, 2015. ACM.

Contact

Please address questions and missing features about the ecr to the author Jakob Bossek j.bossek@gmail.com. Found some nasty bugs? Please use the issue tracker for this. Pay attention to explain the problem as good as possible. At its best you provide an example, so I can reproduce your problem quickly.



jakobbossek/dynvrp documentation built on Jan. 19, 2020, 9:53 p.m.