Construct, Merge, Solve and Adapt Versus Large Neighborhood Search for Solving the Multi-dimensional Knapsack Problem: Which One Works Better When?

DOI10.1007/978-3-319-55453-2_5zbMath1457.90125OpenAlexW2592992628MaRDI QIDQ3304189

Maria J. Blesa, Evelia Lizárraga, Christian Blum

Publication date: 5 August 2020

Published in: Evolutionary Computation in Combinatorial Optimization (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2117/114023

zbMATH Keywords

hybrid algorithmsreducing the search space

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27)

Related Items (2)

Minimum common string partition: on solving large‐scale problem instances ⋮ A comparative analysis of two matheuristics by means of merged local optima networks

Uses Software

• irace

Cites Work

• POPMUSIC as a matheuristic for the berth allocation problem
• Solving large-scale multidimensional knapsack problems with a new binary harmony search algorithm
• Construct, Merge, Solve \& Adapt A new general algorithm for combinatorial optimization
• An efficient preprocessing procedure for the multidimensional 0-1 knapsack problem
• Local branching
• An efficient tabu search approach for the 0-1 multidimensional knapsack problem
• A hybrid simulated annealing metaheuristic algorithm for the two-dimensional knapsack packing problem
• Handbook of metaheuristics
• Variable neighborhood search: Principles and applications

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