Quantum ant colony optimization algorithm for AGVs path planning based on Bloch coordinates of pheromones

DOI10.1007/s11047-018-9711-0zbMath1530.68281OpenAlexW2892024247WikidataQ129217724 ScholiaQ129217724MaRDI QIDQ6151186

Hua-feng Wu, Bo-Wei Xu, Yong-sheng Yang, Jun-jun Li

Publication date: 9 February 2024

Published in: Natural Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11047-018-9711-0

zbMATH Keywords

repulsion factorautomated guided vehicles path planningBloch coordinates of pheromonesquantum ant colony optimization

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Transportation, logistics and supply chain management (90B06) Approximation methods and heuristics in mathematical programming (90C59) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Quantum algorithms and complexity in the theory of computing (68Q12)

Cites Work

• Unnamed Item
• Transport operations in container terminals: literature overview, trends, research directions and classification scheme
• A bilevel decomposition algorithm for simultaneous production scheduling and conflict-free routing for automated guided vehicles
• Dynamic vehicle routing with time windows in theory and practice
• Deadlock prevention for automated guided vehicles in automated container terminals
• Rule-based fuzzy classifier based on quantum ant optimization algorithm

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