Probabilistic and deterministic local search for solving the binary multiknapsack problem

DOI10.1080/02331939508844072zbMath0820.65028OpenAlexW1984643583MaRDI QIDQ4836763

Marida Bertocchi, J. Sobczynska, Agostino Butti, Leon Slominski

Publication date: 21 June 1995

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331939508844072

zbMATH Keywords

comparisonsimulated annealingcomputational experimentstest examplesmultiknapsack problemperformance qualitygreedy-local improvement searchthreshold accept

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Integer programming (90C10) Combinatorial optimization (90C27) Complexity and performance of numerical algorithms (65Y20)

Cites Work

• Optimization by Simulated Annealing
• A thermodynamically motivated simulation procedure for combinatorial optimization problems
• Threshold accepting: A general purpose optimization algorithm appearing superior to simulated annealing
• A simulated annealing approach to the multiconstraint zero-one knapsack problem
• Architectural approach to the IBM 3090E vector performance
• Using simulated annealing to solve routing and location problems

This page was built for publication: Probabilistic and deterministic local search for solving the binary multiknapsack problem