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Learning heuristic selection using a Time Delay Neural Network for Open Vehicle Routing

Raras Tyasnurita, Ender Ozcan, Robert John
2017 2017 IEEE Congress on Evolutionary Computation (CEC)  
This study investigates a learning-via demonstrations approach generating a selection hyper-heuristic for Open Vehicle Routing Problem (OVRP).  ...  A selection hyper-heuristic is a search method that controls a prefixed set of low-level heuristics for solving a given computationally difficult problem.  ...  for solving an open vehicle routing problem (OVRP), a variant of well known vehicle routing problem.  ... 
doi:10.1109/cec.2017.7969477 dblp:conf/cec/TyasnuritaOJ17 fatcat:6kdmphcomvdejna2jljnrzrbxu

A review on Neural Network and Ant Colony Optimization for Vehicle Traffic Analysis and Routing

Er.Manpreet Kaur
2017 International Journal Of Engineering And Computer Science  
An artificial neural network is used for traffic analysis and ant colony optimization is used for finding shortest path.  ...  This paper contains study regarding artificial neural network and ant colony optimization.  ...  Artificial Neural Network: A network inspired by biological neural networks is known as artificial neural network (ANN). Its structure is based on the structure of neurons of human brain.  ... 
doi:10.18535/ijecs/v6i5.26 fatcat:fehjai243jes3mcb2apus6pz74

Learn to Design the Heuristics for Vehicle Routing Problem [article]

Lei Gao, Mingxiang Chen, Qichang Chen, Ganzhong Luo, Nuoyi Zhu, Zhixin Liu
2020 arXiv   pre-print
This paper presents an approach to learn the local-search heuristics that iteratively improves the solution of Vehicle Routing Problem (VRP).  ...  Moreover, the need for expertise and handcrafted heuristics design is eliminated due to the fact that the proposed network learns to design the heuristics with a better performance.  ...  Further research topics include but are not limited to the following suggestions: the network design for other combinatorial optimization problems following this paradigm, especially for the problems where  ... 
arXiv:2002.08539v1 fatcat:yvq3aob7dbhj7oi67okueu5hai

A Pointer Neural Network for the Vehicle Routing Problem with Task Priority and Limited Resources

Yuxiang Sheng, Huawei Ma, Wei Xia
2020 Information Technology and Control  
The vehicle routing problem with task priority and limited resources (VRPTPLR) is a generalized version of the vehicle routing problem (VRP) with multiple task priorities and insufficient vehicle capacities  ...  It is found that the solution time of the pointer neural network is much shorter than that of the genetic algorithm and that the proposed method provides better solutions for large-scale instances.  ...  The authors thank American Journal Experts for English language editing during the preparation of this manuscript.  ... 
doi:10.5755/j01.itc.49.2.24613 fatcat:lmerorii2rcuzh4iz2yeftydlm

Feature and Algorithm Selection for Capacitated Vehicle Routing Problems

Jussi Rasku, Nysret Musliu, Tommi Kärkkäinen
2019 The European Symposium on Artificial Neural Networks  
We propose an extensive feature set for describing capacitated vehicle routing problem instances and illustrate how it can be used in algorithm selection, and how different feature selection approaches  ...  Many exact, heuristic, and metaheuristic algorithms have been proposed to effectively produce high quality solutions to vehicle routing problems.  ...  Automatically selecting the most suitable algorithm for solving Traveling Salesman Problems (TSPs) has been studied for example in [16, 5, 10] and for Vehicle Routing Problems (VRPs) in [8, 11, 21,  ... 
dblp:conf/esann/RaskuMK19 fatcat:ep2jjrs2kjg5vnhh7tre7bhb24

Large Neighborhood Search based on Neural Construction Heuristics [article]

Jonas K. Falkner, Daniela Thyssens, Lars Schmidt-Thieme
2022 arXiv   pre-print
We propose a Large Neighborhood Search (LNS) approach utilizing a learned construction heuristic based on neural networks as repair operator to solve the vehicle routing problem with time windows (VRPTW  ...  Our method uses graph neural networks to encode the problem and auto-regressively decodes a solution and is trained with reinforcement learning on the construction task without requiring any labels for  ...  Neural construction heuristics involve a neural network model, which is trained using the Learning-to-Optimize paradigm.  ... 
arXiv:2205.00772v2 fatcat:x7jaddxjxnf3rphv43upcnm7xm

Characteristic Analysis and Route Optimization of Heterogeneous Neural Network in Logistics Allocation System

Qingju Zeng, Gengxin Sun
2022 Computational Intelligence and Neuroscience  
Aiming at the problems existing in the logistics allocation system, this paper proposes a logistics allocation system model based on a heterogeneous neural network, uses the heterogeneous neural network  ...  to optimize vehicle scheduling, and gives the specific steps to solve the problem of optimal scheduling of distribution vehicles.  ...  Combined with the characteristics of urban tourist data, the heterogeneous neural network community manikin of logistics distribution gadget is selected for complete statistical mastery and training. e  ... 
doi:10.1155/2022/1713183 pmid:35685131 pmcid:PMC9173967 fatcat:bdgjkobzu5cldn2meps2qwa7l4

Analytics and Machine Learning in Vehicle Routing Research [article]

Ruibin Bai and Xinan Chen and Zhi-Long Chen and Tianxiang Cui and Shuhui Gong and Wentao He and Xiaoping Jiang and Huan Jin and Jiahuan Jin and Graham Kendall and Jiawei Li and Zheng Lu and Jianfeng Ren and Paul Weng and Ning Xue and Huayan Zhang
2021 arXiv   pre-print
The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed.  ...  We conclude that ML can be beneficial in enhancing VRP modelling, and improving the performance of algorithms for both online and offline VRP optimisations.  ...  Tyasnurita, Ozcan, and John (2017) used a time delay neural network (TDNN) as a classifier to select the low-level heuristics to solve open vehicle routing problem.  ... 
arXiv:2102.10012v1 fatcat:ihs27x2qu5c55fljxuy4fhawgq

Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem

Jingwen Li, Yining Ma, Ruize Gao, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang
2021 IEEE Transactions on Cybernetics  
for the route construction, which learns to construct a solution by automatically selecting both a vehicle and a node for this vehicle at each step.  ...  Existing deep reinforcement learning (DRL)-based methods for solving the capacitated vehicle routing problem (CVRP) intrinsically cope with a homogeneous vehicle fleet, in which the fleet is assumed as  ...  We first propose a novel attention-based deep neural network to represent the policy, which enables both vehicle selection and node selection at each decision step.  ... 
doi:10.1109/tcyb.2021.3111082 pmid:34554923 fatcat:pmh24zfp3jh6lmuvfoy7gvxweu

Learning to Perform Local Rewriting for Combinatorial Optimization [article]

Xinyun Chen, Yuandong Tian
2019 arXiv   pre-print
Search-based methods for hard combinatorial optimization are often guided by heuristics. Tuning heuristics in various conditions and situations is often time-consuming.  ...  The policy factorizes into a region-picking and a rule-picking component, each parameterized by a neural network trained with actor-critic methods in reinforcement learning.  ...  Figure 4a , NeuRewriter outperforms both heuristic algorithms and the baseline neural network DeepRM.  ... 
arXiv:1810.00337v5 fatcat:dcey2ok4wjfyrjepcwh5rr3wle

A heuristic to generate input sequence for simulated annealing to solve VRP

R. Dhanalakshmi, P. Parthiban, Anirban Ghatak
2010 International Journal of Enterprise Network Management  
This paper addresses the issue of input sequence, which affects the results of simulated annealing (SA) for vehicle routing problem (VRP).  ...  Reference to this paper should be made as follows: Dhanalakshmi, R., Parthiban, P. and Ghatak, A. (2010) 'A heuristic to generate input sequence for simulated annealing to solve VRP', Int.  ...  approach Okonjo-Adigwe (1988) Multi stage Monte Carlo optimisation Conley (1990) Crossbar Hopfield neural network Lo and Bavarian (1993) Tabu search Golden et al. (1997) Adaptive neural network  ... 
doi:10.1504/ijenm.2010.034474 fatcat:cgm2v3bfnjakbmco7c3uo5oxpu

Neural Large Neighborhood Search for the Capacitated Vehicle Routing Problem [article]

André Hottung, Kevin Tierney
2019 arXiv   pre-print
To close this performance gap, we propose a novel large neighborhood search (LNS) framework for vehicle routing that integrates learned heuristics for generating new solutions.  ...  We evaluate our approach on the capacitated vehicle routing problem (CVRP) and the split delivery vehicle routing problem (SDVRP).  ...  We also thank Yuri Malitsky for providing helpful feedback on this paper.  ... 
arXiv:1911.09539v1 fatcat:i53epv7rbzbzpjabfiejztypie

Solving the vehicle routing problem with deep reinforcement learning [article]

Simone Foa and Corrado Coppola and Giorgio Grani and Laura Palagi
2022 arXiv   pre-print
In a second phase, the neural architecture behind the Actor and Critic has been established, choosing to adopt a neural architecture based on the Convolutional neural networks, both for the Actor and the  ...  At this regard, this paper focuses on the application of RL for the Vehicle Routing Problem (VRP), a famous combinatorial problem that belongs to the class of NP-Hard problems.  ...  The neural networks selected were supposed to have at least two fundamental characteristics: as first, they were supposed to be flexible to the input dimension.  ... 
arXiv:2208.00202v1 fatcat:ry2vxse6szatrhtvdf6diz5uni

Dynamic Partial Removal: A Neural Network Heuristic for Large Neighborhood Search [article]

Mingxiang Chen, Lei Gao, Qichang Chen, Zhixin Liu
2020 arXiv   pre-print
This paper presents a novel neural network design that learns the heuristic for Large Neighborhood Search (LNS).  ...  We apply this model to vehicle routing problem (VRP) in this paper as an example.  ...  For example, Network Flow problem, Vehicle Routing problems, Generalized Assignment problems, etc, can be depicted in this way.  ... 
arXiv:2005.09330v1 fatcat:fa33rentqra5dbpezd2mptyymu

Order Crossover for the Inventory Routing Problem

Mohamed Salim Amri Sakhri, Mounira Tlili, Hamid Allaoui, Ouajdi Korbaa
2018 The European Symposium on Artificial Neural Networks  
In this paper, we aim to find a solution that reduces the logistical activity costs by using new hybrid meta-heuristics.  ...  The operator considered is the Order Crossover (OX); we will test our hybrid algorithm in a Periodic Inventory Routing Problem (PIRP).  ...  For each heuristic, the best results for each set of instances were averaged following a test cases.  ... 
dblp:conf/esann/SakhriTAK18 fatcat:tkeqfm7bijfmdluc4ixhelfkdu
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