Improving neighborhood exploration into MOEA/D framework to solve a bi-objective routing problem

DOI10.1111/itor.13373MaRDI QIDQ6609702

Diego Cattaruzza, Laetitia Jourdan, Clément Legrand, Unnamed Author

Publication date: 24 September 2024

Published in: International Transactions in Operational Research (Search for Journal in Brave)

zbMATH Keywords

local searchmultiobjective optimizationrouting problemsMOEA/Dautomatic configuration

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Cites Work

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• A hybrid algorithm for a class of vehicle routing problems
• A decomposition based memetic algorithm for multi-objective vehicle routing problem with time windows
• A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem
• Designing granular solution methods for routing problems with time windows
• Knowledge-guided local search for the vehicle routing problem
• New benchmark instances for the capacitated vehicle routing problem
• A simple and effective evolutionary algorithm for the vehicle routing problem
• Multi-objective vehicle routing problems
• A unified solution framework for multi-attribute vehicle routing problems
• The Granular Tabu Search and Its Application to the Vehicle-Routing Problem
• Vehicle Routing
• Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints
• Multi-Objective Combinatorial Optimization: Problematic and Context

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