Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.7954

@Article{MacLachlan:ECJ:gphh,

• author = "Jordan MacLachlan and Yi Mei and Juergen Branke and Mengjie Zhang",
• title = "Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems",
• journal = "Evolutionary Computation",
• year = "2020",
• volume = "28",
• number = "4",
• pages = "563--593",
• month = "Winter",
• keywords = "genetic algorithms, genetic programming, Arc Routing, Hyper Heuristic, Stochastic Optimisation",
• ISSN = "1063-6560",
• URL = "https://doi.org/10.1162/evco_a_00267",
• DOI = "doi:10.1162/evco_a_00267",
• size = "32 pages",
• abstract = "Due to its direct relevance to post-disaster operations, meter reading and civil refuse collection, the Uncertain Capacitated Arc Routing Problem (UCARP) is an important optimisation problem. Stochastic models are critical to study as they more accurately represent the real-world than their deterministic counterparts. Although there have been extensive studies in solving routing problems under uncertainty, very few have considered UCARP, and none consider collaboration between vehicles to handle the negative effects of uncertainty. This paper proposes a novel Solution Construction Procedure (SCP) that generates solutions to UCARP within a collaborative, multivehicle framework. It consists of two types of collaborative activities: one when a vehicle unexpectedly expends capacity (route failure), and the other during the refill process. Then, we propose a Genetic Programming Hyper-Heuristic (GPHH) algorithm to evolve the routing policy used within the collaborative framework. The experimental stu",
• notes = "School of Engineering and Computer Science, Victoria University of Wellington,PO Box 600, Wellington 6140, New Zealand",

}

Genetic Programming entries for Jordan MacLachlan Yi Mei Jurgen Branke Mengjie Zhang

Citations