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Hybridizations of evolutionary algorithms with Large Neighborhood Search
Computer Science Review, 2022Recent developments of evolutionary algorithms (EAs) for discrete optimization problems are often characterized by the hybridization of EAs with local search methods, in particular, with Large Neighborhood Search. In this survey, we consider some of the most promising directions of this kind of hybridization and provide examples in the context of well ...
Christian Blum 0001 +2 more
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Neural large neighborhood search for routing problems
Artificial Intelligence, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
André Hottung, Kevin Tierney
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Principles for the Design of Large Neighborhood Search
Journal of Mathematical Modelling and Algorithms, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tom Carchrae, J. Christopher Beck
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Propagation Guided Large Neighborhood Search
2004In this article, we explore how neighborhoods for the Large Neighborhood Search (LNS) framework can be automatically defined by the volume of propagation of our Constraint Programming (CP) solver. Thus we can build non trivial neighborhoods which will not be reduced to zero by propagation and whose size will be close to a parameter of the search ...
Laurent Perron +2 more
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Large neighborhood search for LNG inventory routing
Journal of Heuristics, 2012Liquefied Natural Gas (LNG) is steadily becoming a common mode for commercializing natural gas. Due to the capital intensive nature of LNG projects, the optimal design of LNG supply chains is extremely important from a profitability perspective. Motivated by the need for a model that can assist in the design analysis of LNG supply chains, we address an
Vikas Goel +3 more
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Very Large-Scale Neighborhood Search
2021Very Large-Scale Neighborhood Search is not an algorithm or a class of algorithms, but rather a conceptual framework which can be used for solving combinatorial optimization problems. The approach “concentrates on neighborhood search algorithms where the size of the neighborhood is ‘very large’ with respect to the size of the input data.” Typically ...
Maniezzo, Vittorio +2 more
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A Multi-paradigm Tool for Large Neighborhood Search
2013We present a general tool for encoding and solving optimization problems. Problems can be modeled using several paradigms and/or languages such as: Prolog, MiniZinc, and GECODE. Other paradigms can be included. Solution search is performed by a hybrid solver that exploits the potentiality of the Constraint Programming environment GECODE and of the ...
CIPRIANO, Raffaele +2 more
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Large Neighborhood Search for Dial-a-Ride Problems
2011Dial-a-Ride problems (DARPs) arise in many urban transportation applications. The core of a DARP is a pick and delivery routing with multiple vehicles in which customers have ride-time constraints and routes have a maximum duration. This paper considers DARPs for which the objective is to minimize the routing cost, a complex optimization problem which ...
Siddhartha Jain 0001 +1 more
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A Large Neighborhood Search Heuristic for Graph Coloring
2007We propose a new local search heuristic for graph coloring that searches very large neighborhoods. The heuristic is based on solving a MAX-CUT problem at each step. While the MAX-CUT problem is formally hard, fast heuristics that give "good" cuts are available to solve this. We provide computational results on benchmark instances. The proposed approach
Michael A. Trick, Hakan Yildiz
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Adaptive large neighborhood search for scheduling of mobile robots
Proceedings of the Genetic and Evolutionary Computation Conference, 2019Our work addresses the scheduling of mobile robots for transportation and processing of operations on machines in a flexible manufacturing system. Both mobile robots and automated guided vehicles (AGVs) can transport components among machines in the working space.
Quang-Vinh Dang 0002 +2 more
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