Genetic Programming with Activity Group Selection for Dynamic Multi-mode Resource-Constrained Project Scheduling Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.8638

@InProceedings{DBLP:conf/cec/TianMZ25,

• author = "Yuan Tian and Yi Mei and Mengjie Zhang",
• title = "Genetic Programming with Activity Group Selection for Dynamic Multi-mode Resource-Constrained Project Scheduling Problems",
• booktitle = "2025 IEEE Congress on Evolutionary Computation (CEC)",
• year = "2025",
• editor = "Yaochu Jin and Thomas Baeck",
• address = "Hangzhou, China",
• month = "8-12 " # jun,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, Processor scheduling, Scalability, Heuristic algorithms, Decision making, Evolutionary computation, Dynamic scheduling, Dynamic programming, Project Scheduling, Multiple Modes, Hyperheuristics, Decision-making",
• isbn13 = "979-8-3315-3432-5",
• timestamp = "Tue, 08 Jul 2025 01:00:00 +0200",
• biburl = "https://dblp.org/rec/conf/cec/TianMZ25.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• URL = "https://doi.org/10.1109/CEC65147.2025.11042979",
• DOI = "10.1109/CEC65147.2025.11042979",
• abstract = "Efficient scheduling under uncertain durations and constrained resources remains a core challenge in the dynamic multi-mode resource-constrained project scheduling problem. Genetic programming (GP) has proven effective for evolving scheduling rules; however, conventional strategies often assess activities separately, disregarding potential synergies among modes of concurrently executable tasks. To overcome this limitation, we develop a group-based strategy that selects from feasible combinations of activity-mode tuples. New terminals are designed to capture the attributes of these combinations and embed them into a GP framework. Experimental evaluation across multiple scenarios demonstrates that our group-based GP approach outperforms conventional GP methods based on individual activity prioritisation.",
• notes = "also known as \cite{tian:2025:CEC} \cite{11042979}",

}

Genetic Programming entries for Yuan Tian Yi Mei Mengjie Zhang

Citations