- author = "Yuxin Liu and Yi Mei and Mengjie Zhang and Zili Zhang",
- title = "A Predictive-Reactive Approach with Genetic Programming and Cooperative Co-evolution for Uncertain Capacitated Arc Routing Problem",
- journal = "Evolutionary Computation",
- year = "2020",
- volume = "28",
- number = "2",
- pages = "289--316",
- month = "Summer",
- keywords = "genetic algorithms, genetic programming, Capacitated arc routing problem, cooperative co-evolution, hyper-heuristics",
- ISSN = "1063-6560",
-
DOI = "
doi:10.1162/evco_a_00256",
- size = "25 pages",
- abstract = "The uncertain capacitated arc routing problem is of great significance for its wide applications in the real world. In uncertain capacitated arc routing problem, variables such as task demands and travel costs are realised in real time. This may cause the predefined solution to become ineffective and/or infeasible. There are two main challenges in solving this problem. One is to obtain a high-quality and robust baseline task sequence, and the other is to design an effective recourse policy to adjust the baseline task sequence when it becomes infeasible and/or ineffective during the execution. Existing studies typically only tackle one challenge (the other being addressed using a naive strategy). No existing work optimises the baseline task sequence and recourse policy simultaneously. To fill this gap, we propose a novel proactive-reactive approach, which represents a solution as a baseline task sequence and a recourse policy. The two components are optimised under a cooperative co-evol",
-
notes = "Supplemental Material
https://www.mitpressjournals.org/doi/suppl/10.1162/evco_a_00256
Also know as \cite{DBLP:journals/ec/LiuMZZ20}",
