Introducing look-ahead into relocation rules generated with genetic programming for the container relocation problem

Created by W.Langdon from gp-bibliography.bib Revision:1.8528

@Article{Durasevic:2025:GPEM,

• author = "Marko Durasevic and Mateja Dumic and Francisco Javier {Gil Gala} and Domagoj Jakobovic",
• title = "Introducing look-ahead into relocation rules generated with genetic programming for the container relocation problem",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2025",
• volume = "26",
• pages = "Article no: 26",
• note = "Online first",
• keywords = "genetic algorithms, genetic programming, Container relocation problem, Relocation rules",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-025-09523-8",
• abstract = "manually designing effective RRs is challenging, leading to the use of genetic programming to generate them automatically. A key limitation of both manually and automatically designed RRs is their restricted problem view and limited decision-making scope. This often results in suboptimal relocations, negatively impacting future operations and overall efficiency. A crucial aspect of RR design is defining effective relocation schemes that enhance decision-making by considering the long-term impact of relocations. This study investigates several relocation schemes that provide RRs with lookahead capabilities, enabling them to anticipate future consequences and make more informed moves. In addition to two standard schemes, four novel relocation schemes are introduced and evaluated using an established problem set. The results demonstrate that properly adapting relocation schemes can significantly enhance the performance of automatically designed RRs, leading to significantly better results.",
• notes = "Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, Zagreb, 10000, Croatia",

}

Genetic Programming entries for Marko Durasevic Mateja Dumic Francisco Javier Gil Gala Domagoj Jakobovic

Citations