Solving constrained combinatorial optimization problems via importance sampling in the grand canonical ensemble

DOI10.1016/j.cpc.2004.10.003zbMath1196.90107OpenAlexW2014970962MaRDI QIDQ709664

Karl-Heinz Zimmermann

Publication date: 18 October 2010

Published in: Computer Physics Communications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cpc.2004.10.003

zbMATH Keywords

combinatorial optimizationMonte Carlo simulationknapsack problemstatistical mechanicsgrand canonical ensemble

Mathematics Subject Classification ID

Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Combinatorial optimization (90C27)

Uses Software

• Maple

Cites Work

• A complete anytime algorithm for number partitioning
• Note on two theorems in nonequilibrium statistical mechanics
• Fast Approximation Algorithms for the Knapsack and Sum of Subset Problems
• Equation of State Calculations by Fast Computing Machines
• Determining computational complexity from characteristic ‘phase transitions’
• Statistical mechanics methods and phase transitions in optimization problems
• A physicist's approach to number partitioning
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