Solving the maximum edge disjoint path problem using a modified Lagrangian particle swarm optimisation hybrid

DOI10.1016/j.ejor.2021.01.009zbMath1487.90574OpenAlexW3121006322MaRDI QIDQ2030326

Kalyanmoy Deb, Andreas T. Ernst, Xiaodong Li, Jake Weiner, Yu-An Sun

Publication date: 7 June 2021

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2021.01.009

zbMATH Keywords

combinatorial optimizationmetaheuristicslarge scale optimization

Mathematics Subject Classification ID

Programming involving graphs or networks (90C35) Large-scale problems in mathematical programming (90C06) Communication networks in operations research (90B18) Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27)

Related Items (3)

Generalizations, formulations and subgradient based heuristic with dynamic programming procedure for target set selection problems ⋮ Design of survivable wireless backhaul networks with reliability considerations ⋮ Solving the inverse graph model for conflict resolution using a hybrid metaheuristic algorithm

Uses Software

• COMET
• irace
• pyrgg

Cites Work

• A note on two problems in connexion with graphs
• LS(graph): a constraint-based local search for constraint optimization on trees and paths
• New bundle methods for solving Lagrangian relaxation dual problems
• Escaping a grid by edge-disjoint paths
• Approximating disjoint-path problems using packing integer programs
• The volume algorithm: Producing primal solutions with a subgradient method
• The cavity method at zero temperature
• An algorithm for large scale 0-1 integer programming with application to airline crew scheduling
• Finding edge-disjoint paths in networks: an ant colony optimization algorithm
• Efficient routing in all-optical networks
• The Lagrangian Relaxation Method for Solving Integer Programming Problems
• Reducibility among Combinatorial Problems
• Solving the edge‐disjoint paths problem using a two‐stage method

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