Combining biased randomization with iterated local search for solving the multidepot vehicle routing problem

DOI10.1111/itor.12101zbMath1332.90067OpenAlexW2084461063MaRDI QIDQ2794677

Daniel Guimarans, Iñaki Pascual, Barry Barrios, Angel A. Juan

Publication date: 11 March 2016

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

Full work available at URL: https://doi.org/10.1111/itor.12101

zbMATH Keywords

metaheuristicsrandomized algorithmsiterated local searchbiased randomizationmultidepot vehicle routing problemparallelization of heuristics

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Traffic problems in operations research (90B20)

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Uses Software

• VRP
• METSlib

Cites Work

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• Using parallel \& distributed computing for real-time solving of vehicle routing problems with stochastic demands
• Combining probabilistic algorithms, constraint programming and Lagrangian relaxation to solve the vehicle routing problem
• The multi-depot vehicle routing problem with inter-depot routes
• A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows
• A general heuristic for vehicle routing problems
• The vehicle routing problem. Latest advances and new challenges.
• A modular algorithm for an extended vehicle scheduling problem
• A simple and effective evolutionary algorithm for the vehicle routing problem
• A tabu search heuristic for the multi-depot vehicle routing problem
• What you should know about the vehicle routing problem
• Implementing vehicle routing algorithms
• A New Heuristic for the Multi-Depot Vehicle Routing Problem that Improves upon Best-Known Solutions
• A tabu search heuristic for periodic and multi-depot vehicle routing problems
• A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems
• Using iterated local search for solving the flow‐shop problem: Parallelization, parametrization, and randomization issues
• A biased‐randomized algorithm for the two‐dimensional vehicle routing problem with and without item rotations
• Computer Solutions of the Traveling Salesman Problem
• An Upperbound Algorithm for the Single and Multiple Terminal Delivery Problem
• A multiple-depot, multiple-vehicle, location-routing problem with stochastically processed demands