Augmented neural networks and problem structure-based heuristics for the bin-packing problem

DOI10.1080/00207721.2010.549587zbMath1305.90214OpenAlexW1975654268MaRDI QIDQ5497425

Anurag Agarwal, Nihat Kasap

Publication date: 4 February 2015

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2010.549587

zbMATH Keywords

heuristicsneural networksoptimisationbin packing

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Stochastic scheduling theory in operations research (90B36)

Related Items (1)

A hybrid neural network approach to minimize total completion time on a single batch processing machine

Cites Work

• NeuroGenetic approach for combinatorial optimization: an exploratory analysis
• Two heuristics for the one-dimensional bin-packing problem
• Exact solution of bin-packing problems using column generation and branch-and-bound
• Bin-packing by simulated annealing
• BISON: A fast hybrid procedure for exactly solving the one-dimensional bin packing problem
• Augmented neural networks for task scheduling.
• A hybrid approach for optimization of one-dimensional cutting
• Hybrid genetic algorithms for bin-packing and related problems
• Theoretical insights into the augmented-neural-network approach for combinatorial optimization
• Solving the one-dimensional bin packing problem with a weight annealing heuristic
• Worst-Case Analysis of Heuristics for the Bin Packing Problem with General Cost Structures
• A morph-based simulated annealing heuristic for a modified bin-packing problem
• New heuristics for one-dimensional bin-packing

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