Scientific applications of LKH

M. Abdel-Basset ,R. Mohamed, K. M. Sallam, and R. K. Chakrabortty,
An Efficient-Assembler Whale Optimization Algorithm for DNA Fragment
Assembly Problem: Analysis and Validations.
IEEE Access, vol. 8, pp. 222144-222167, 2020.

F. Abedi, D. W. Morris, J. Rezaee, and M. R. Salarian,
Cayley graphs of order 8pq are hamiltonian.
arXiv:2304.03348 [math.CO], 2023.

N. Absi and C. Archetti and S. Dauzère-Pérès and D. Feillet, and B. Ahrens,
A two-phase iterative heuristic approach for the Production Routing Problem.
Working Papers, University of Brescia, WPDEM 2013/8, 2013.

L. Accorsi and D. Vigo,
A Fast and Scalable Heuristic for the Solution of Large-Scale Capacitated
Vehicle Routing Problems.
Research report, OR-20-2, University of Bologna, 2020.

L. Accorsi,
Innovative Hybrid Approaches for Vehicle Routing Problems.
Ph.D. thesis, Univesity of Bologna, 2022.

R. Aciu and H. Ciocarlie,
G-code optimization algorithm and its application on printed circuit board drilling.
9th IEEE International Symposium on Applied Computational Intelligence and
Informatics (SACI), pp. 43-47, 2014.

S. Agarwal and S. Akella,
The Single Robot Line Coverage Problem: Theory, Algorithms and Experiments.
NETWORKS, 2023.

B. Ahrens,
A tour construction framework for the travelling salesman problem.
Ph.D. thesis, Nova Southeastern University, 2012.

R. K. Ahuja, O. Ergun, J. B. Orlin, and A. P. Punnen,
A survey of very large scale neighborhood search techniques.
Discrete Applied Mathematics 123, pp. 75-102, 2002.

K. Akbudak, E. Kayaaslan, and C. Aykanat,
Hypergraph-Partitioning-Based Models and Methods for Exploiting Cache Locality in
Sparse-Matrix Vector Multiplication.
Technical Report, BU-CE-1201, Bilkent University, 2012.

F. M. al-Rifaie and M. M. al-Rifaie,
Maximising overlap score in DNA sequence assembly problem by Stochastic
Diffusion Search.
SAI Inteligent Systems Conference, pp. 301-322, 2015.

K. Alexis, C. Papachristos, and R. Siegwart,
Uniform coverage structural inspection path–planning for micro aerial vehicles.
IEEE International Symposium on Intelligent Control, 2015.

K. Alexis, G. Darivianakis, M. Burri, and Roland Siegwart,
Aerial robotic contact-based inspection: planning and control.
Autonomous Robots, Voume 40, Issue 4, pp. 631-655, 2016.

K. Alexis, C. Papachristos, R. Siegwart, and A. Tzes,
Distributed Infrastructure Inspection Path Planning subject to Time Constraints.
arXiv:1612.08245 [cs.RO], 2016.

K. Alexis,
Aerial Drop of Robots and Sensors for Optimal Area Coverage.
arXiv:1711.10159 [cs.RO], 2017.

Z. A. Allen,
Use of traveling salesman problem solvers in the construction of genetic linkage maps.
M.Sc. thesis, Colorado State University, 2015.

M. Allaoui, B. Ahiod, and M. El Yafrani,
A hybrid crow search algorithm for solving the DNA fragment assembly problem.
Expert Systems with Applications, Volume 102, pp. 44-56, 2018.

R. Almadhoun, T. Taha, L. Seneviratne, J. Dias, and G. Cai,
A survey on inspecting structures using robotic systems.
International Journal of Advanced Robotic Systems, November-Dember 2016.

R. Almadhoun, T. Taha, D. Gan, J. Dias, Y. Zweiri, and L. Seneviratne,
Coverage Path Planning with Adaptive Viewpoint Sampling to Construct 3D
Models of Complex Structures for the Purpose of Inspection.
International Conference on Intelligent Robots and Systems, 2018.

R. Almadhoun, T. Taha, J. Dias, L. Seneviratne, and Y. Zweiri,
Coverage Path Planning for Complex Structures Inspection Using Unmanned
Aerial Vehicle (UAV).
ICIRA 2019, Lecture Notes in Computer Science, Vol. 11744, pp 243-266, 2019.

S. C. L. Ammann, B. Ostermann, S. Stiller, and T. de Wolff,
A Speed-up for Helsgaun's TSP Heuristic by Relaxing the Positive Gain Criterion.
arXiv:2401.16149 [math.OC], 2024..

B. Alper, N. H. Riche, G. Ramos, and M. Czerwinski,
Design Study of LineSets, a Novel Set Visualization Technique.
IEEE Transactions on Visualization and Computer Graphics, pp. 2259-2267, 2011.

S. Alshammari, S. Song, and B. -Y. Choi,
HiCARE: Hierarchical Clustering Algorithm for Road Service Routing Enhancement.
IEEE Access, 2023.

M. E. J. Amarel et al.,
A first generation whole genome RH map of the river buffalo with comparison to
domestic cattle.
BMC Genomics 9, No. 1, 2008.

R. P. Anderson and D. Milutinovic,
The Dubins Traveling Salesperson Problem with Stochastic Dynamics.
6th Annual Dynamic Systems and Control Conference, 2013.

C. E. Andrade, F. K. Miyazawa, and M. G. C. Resende,
Evolutionary algorithm for the k-interconnected multi-depot multi-traveling salesmen
problem.
GECCO 2013: 463-470.

D. Apiletti, E. Baralis, and T. Cerquitelli,
Energy-saving models for wireless sensor networks.
Knowledge and Information Systems, pp. 1-30, 2010.

D. L. Applegate, R. E. Bixby, V. Chvatal, W. Cook, D. G. Espinoza,
M. Goycoolea, and K. Helsgaun,
Certification of an optimal TSP tour through 85,900 cities.
Operations Research Letters, 37, pp. 11-15, 2009.

D. L. Applegate, R. E. Bixby, V. Chvátal, and W. J. Cook,
The Traveling Salesman Problem: A Computational Study.
Princeton University Press, 2006.

A. Arbelaez, C. Truchet, B. O'Sullivan,
Learning Sequential and Parallel Runtime Distributions for Randomized Algorithms.
International Conference on Tools with Artificial Intelligence, 2016.

A. Arbelaez and B. O’Sullivan,
Learning a Stopping Criterion for Local Search.
LION 2016, LNCS 10079, pp. 3-16, 2016.

C. Archetti, D. Feillet, A. Mor, and M. G. Speranza,
An iterated local search for the traveling salesman problem with release dates and
completion time minimization.
Computers and Operations Research, doi: 10.1016/j.cor.2018.05.001, 2018.

C. Archetti, E. Fernández, and D. L. Huerta-Muñoz,
A two-phase solution algorithm for the Flexible Periodic Vehicle Routing Problem.
Computers and Operations Research, doi: 10.1016/j.cor.2018.05.021, 2018.

C. Archetti, D. Feillet, A. Mor, and M. G. Speranza,
Dynamic traveling salesman problem with stochastic release dates.
European Journal of Operational Research, In Press, 2019.

F. Arnold,
Efficient heuristics for routing and integrated logistics.
Ph.D thesis, Universiteit Antwerpen, 2018.

F. Arnold, M. Gendreau, K. Sörensen,
Efficiently solving very large-scale routing problems.
Computers and Operations Research, Vol. 107, pp. 32–42, 2019.

S Arshad,
Sequence Based Memetic Algorithms for Static and Dynamic Travelling Salesman
Problems.
Ph.D. thesis, University of Leicester, 2012.

A. B. Asghar, S. L. Smith, and S. Sundaram,
Multi-Robot Routing for Persistent Monitoring with Latency Constraints.
arXiv:1903.06105 [cs.RO], 2019.

A. B. Asghar, S. Sundaram, and S, L. Smith,
Multi-Robot Persistent Monitoring: Minimizing Latency and Number of Robots
with Recharging Constraints.
arXiv:2303.08935 [cs.RO], 2023.

M. Avci, M. G. Avci, and A. Hamzadayı,
A branch-and-cut approach for the distributed no-wait flowshop scheduling problem.
In Press, Computers & Operations Research, 2022.

S. M. Avdoshin and E. N. Beresneva,
The Metric Travelling Salesman Problem: The Experiment On Pareto-optimal Algorithms.
Trudy ISP RAN/Proc. ISP RAS, vol. 29, issue 4, pp. 123-138, 2017.

L. Babel,
New heuristic algorithms for the Dubins traveling salesman problem.
Journal of Heuristics, https://doi.org/10.1007/s10732-020-09440-2, 2020.

F. Bachmann, H. Schaeben, and R. Hielscher,
Optimizing the experimental design of texture goniometry.
Journal of Applied Crystallography. Vol. 45, pp. 1173-1181, 2012.

J. Bae and S. Rathinam,
Approximation Algorithm for a Heterogeneous Vehicle Routing Problem.
International Journal of Advanced Robotic Systems, 12:113, DOI: 10.5772/60086, 2015.

J. Bae and W. Chung,
A Heuristic for a Heterogeneous Automated Guided Vehicle Routing Problem.
International Journal of Precision Engineering and Manufacturing, Vol. 18, No. 6,
pp. 795-801, 2017.

J. Bae and W. Chung,
A Heuristic for Path Planning of Multiple Heterogeneous Automated Guided Vehicles.
International Journal of Precision Engineering and Manufacturing, Vol. 19, No. 12,
pp. 1765-1771, 2018.

J. Bae and W. Chung,
Efficient path planning for multiple transportation robots under various loading conditions.
International Journal of Advanced Robotic Systems, DOI: 10.1177/172988, 2019.

J. Bae and W. Chung,
Heuristics for Two Depot Heterogeneous Unmanned Vehicle Path Planning to
Minimize Maximum Travel Cost.
Sensors. Vol. 19, No. 11, 2019.

D. H. Baik and K. K. Saluja,
Progressive random access scan: a simultaneous solution to test power, test data volume
and test time.
Proceedings of IEEE International Test Conference, pp. 272-277, 2005.

M. L. Baker, M. R. Baker, C. F. Hryc, T. Ju, and W. Chiu,
Gorgon and pathwalking: Macromolecular modeling tools for subnanometer resolution
density maps.
Biopolymers, 97(9), pp. 655-668, 2012.

M. L. Baker, C. F. Hryc, Q. Zhang, W. Wu, J. Jakana, C. Haase-Pettingell, P. V. Afonine,
P. D. Adams, J. A. King, W. Jiang, and W. Chiu,
Validated near-atomic resolution structure of bacteriophage epsilon15 derived from
cryo-EM and modeling.
Proc. Natl. Acad. Sci. U S A., 110(30), pp.12301-12306, 2013.

M. R. Baker, I. Rees, S. J. Ludtke, W. Chiu.,and M. L. Baker,
Constructing and validating initial Cα models from subnanometer resolution density
maps with pathwalking.
Structure, 20(3), pp. 450-463, 2012.

P. Baniasadi,
Algorithms for Solving Variations of the Traveling Salesman Problem.
Ph.D. thesis, Flinders University, 2019.

P. Baniasadi, M. Foumani, K. Smith-Miles, and V. Ejov,
A transformation technique for the clustered generalized traveling salesman
problem with applications to logistics.
European Journal of Operational Research, Volume 285, Issue 2, p. 444-457, 2020.

P. Baniasadi, V. Ejov, J. A. Filar, M. Haythorpe, and S. Rossomakhine,
Deterministic “Snakes and Ladders” Heuristic for the Hamiltonian cycle problem.
Mathematical Programming Computation, September 2013.

P. Baniasadi, V. Ejov, J. A. Filar, M. Haythorpe, and S. Rossomakhine,
A new benchmark set for Traveling salesman problem and Hamiltonian cycle problem.
arXiv:1806.09285, [cs.DS], 2018.

S. Banik, S. Rathinam, and P. B. Sujit,
Min-Max Path Planning Algorithms for Heterogeneous, Autonomous Underwater Vehicles.
IEEE/OES Autonomous Underwater Vehicle Workshop (AUV), pp. 1-6, 2018.

S. Banik, P. B. Sujit, and S. Rathinam,
Multi-AUV Coverage with Functional Constraints and Currents.
2020 IEEE/OES Autonomous Underwater Vehicles Symposium, 2020.

D. Barbucha, I. Czarnowski, P. Jȩdrzejowicz, E. Ratajczak-Ropel, and I. Wierzbowska,
e-JABAT - An Implementation of the Web-Based A-Team.
Intelligent Agents in the Evolution of Web and Applications, pp. 57-86, 2009.

U. Baroudi, M. Alshaboti, A. Koubaa, and S. Trigui,
Dynamic Multi-Objective Auction-Based (DYMO-Auction) Task Allocation.
Applied Scences, 10(9), 2020.

R. Barreira and J. C. Garcia,
Optimal Object Retrieval Paths in Indoor Spaces.
Report, Instituto Superior Técnico Lisboa, Portugal, 2018.

S. Basu and M. Sharma,
Preprocessing Schemes for Tabu search on Asymmetric Traveling Salesman Problem.
Working paper, Indian Institute of Management Calcutta, WPS-735, 2013.

S. Basu, M. Sharma, and P. S. Ghosh,
Efficient preprocessing methods for tabu search: an application on asymmetric travelling
salesman problem.
INFOR, Volume 55, Issue 2, pp. 134-158, 2017.

N. T. Bauduin,
Multi-Hybrid Algorithm for Searching Solutions to Optimization Problems:
Case of Traveling Salesman Problem (TSP).
EasyChair, Preprint no. 4491, 2020.

R. Bazylevych, B. Prasad, R. Kutelmakh, R. Dupas, and L. Bazylevych,
Decomposition and Scanning Optimization Algorithms for TSP.
TMFCS, 2008.

R. Bazylevych, B. Prasad, R. Kutelmakh, R. Dupas, and L. Bazylevych,
A Decomposition Algorithm for Uniform Traveling Salesman Problem.
Proceedings of IICAI-09, pp. 47-56, 2009.

R. Bazylevych, R. Dupas, B. Prasad, B. Kuz, R. Kutelmakh, and L. Bazylevych,
A Parallel Approach for Solving a Large-Scale Traveling Salesman Problem.
Proceedings of IICAI-11 pp. 566-579, 2011.

R. Bazylevych, B. Kuz, R. Kutelmakh, R. Dupas, B. Prasad, Y. Haxhimusa, and L, Bazylevych,
A Parallel Ring Method for Solving a Large-scale Traveling Salesman Problem.
International Journal of Information Technology and Computer Science, Vol. 8, No. 5, 2016.

R. Bazylevych, R. Kutelmakh, and B. Prasad,
Software Architecture for Solving Large-scale Traveling Salasmen Problem.
Modern engineering and innovative technologies, No. 26-01, 2023.

R. Bähnemann, N. Lawrance, J. J. Chung, M. Pantic, R. Siegwart, and J. Nieto,
Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling
Salesman Problem.
arXiv:1907.09224 [cs.RO], 2019.

A. Bdeir, S. Boeder, T. Dernedde, K. Tkachuk, J. K. Falkner, and L. Schmidt-Thieme,
RP-DQN: An application of Q-Learning to Vehicle Routing Problems.
arXiv:2104.12226 [cs.LG], 2021.

M. Behroozi and D. Ma,
Crowdsourced Delivery with Drones in Last Mile Logistics.
ATMOS, Article No. 17, pp. 17:1–17:12, 2020.

M. Behroozi and D. Ma,
Last Mile Delivery with Drones and Sharing Economy.
arXiv:2308.16408 [math.OC], 2023.

M. J. Beimers,
Tour merging via tree decomposition.
M.Sc. thesis, Utrecht University, 2015.

R. Bekker, B. Bharti, L. Lan, and M. Mandjes,
A queueing-based approach for integrated routing and appointment scheduling.
arXiv:2312.02715 [math.OC], 2023.

I. Bello, H. Pham, Q. V. Le, M. Norouzi, and S. Bengio,
Neural Combinatorial Optimization with Reinforcement Learning.
Under review as a conference paper at ICLR, 2017

P. Benchimol, W-J. Hoeve, J-C. Régin, L-M. Rousseau, and M.l Rueher,
Improved filtering for weighted circuit constraints.
Constraints, Vol. 17, Number 3, pp. 1-29, 2012.

P. Beraldi and M. E. Bruni,
A stochastic programming approach for the traveling purchaser problem,
IMA Journal of Management Mathematics, pp. 1-23, 2015.

E. Beresneva and S. Avdoshin,
Local search metaheuristics for Capacitated Vehicle Routing Problem:
a comparative study.
Proceedings of SYRCoSE, pp. 109-117, 2019.

E. Beresneva and S. Avdoshin,
Analysis of Mathematical Formulations of Capacitated Vehicle Routing Problem
and Methods for their Solution.
Trudy ISP RAN/Proc. ISP RAS, vol. 30, issue 3, pp. 233-250, 2018.

E. N. Beresneva and S. M. Avdoshin,
Pareto-optimal Algorithms for Metric TSP: Experimental Research.
International Journal of Open Information Technologiesm vol. 5, no .5, 2017.

J. A. Bernal-Moyano, J. W. Escobar, C. Marín-Moreno, R. Linfati, and G. Gatica,
A Computational Comparision of Heuristic Algorithmsfor the Location-Routing Problem
with Heterogenous Fleet (LRPH).
DYNA, vol. 84, no. 200, pp. 193-201, 2017.

J. A. Bernal-Moyano, J. W. Escobar, C. Marín-Moreno, R. Linfati, and G. Gatica,
A comparison of trajectory granular based algorithms for the location-routing problem
with heterogeneous fleet (LRPH).
DYNA, Volume 84, Issue 200, pp. 193-201, 2017.

A. Bertagnon and M. Gavanelli,
Improved Filtering for the Euclidean Traveling Salesperson Problem in CLP(FD).
Proceedings of the AAAI Conference on Artificial Intelligence 34(02), pp. 1412-1419, 2020.

A. Bertagnon,
Constraint Programming Algorithms for Route Planning Exploiting Geometrical Information.
arXiv:2009.10253 [cs.AI], 2020.

A. Bevilaqua, D. Bevilaqua, and K. Yamanaka,
Parallel island based memetic algorithm with Lin-Kernighan local search for a real-life
Two-Echelon heterogeneous vehicle routing problem based on brazilian wholesale companies.
Applied Soft Computing, Volume 56, pp. 697-711, 2019.

L. A. Bewoor, V. Chandraprakash, and S. U. Sapkal,
Evolutionary hybrid particle swarm optimization algorithm to minimize makespan to schedule
a flow shop with no wait.
Journal of Engineering Science and Technology, Vol. 14, Issue2, pp. 609-628, 2019.

J. Bi, Y. Ma, J. Wang, Z. Cao, J. Chen, Y. Sun, and Y. M. Chee,
Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation.
arXiv:2210.07686 [cs.LG], 2022.

Y. Bian, H. Zhu, and Z. Lou,
Online Large-scale Garbage Collection Scheduling: A Divide-and-conquer Approach.
ICPADS, pp. 395-402, 2023.

A. Bircher, K. Alexis, M. Burri, P. Oettershagen, S. Omari, T. Mantel, and R. Siegwart,
Structural Inspection Path Planning via Iterative Viewpoint Resampling with Application
to Aerial Robotics.
IEEE International Conference on Robotics & Automation, 2015.

A. Bircher, M. Kamel, K. Alexis, M. Burri1, P. Oettershage, S. Omari, T. Mantel , and R. Siegwart,
Three-dimensional coverage path planning via viewpoint resampling and tour optimization
for aerial robots.
Autonomous Robots, pp. 1-20, 2015.

A. Blazinskas and A. Misevicius,
Generating High Quality Candidate Sets by Tour Merging for the Traveling Salesman Problem.
Communications in Computer and Information Science, Volume 319, Part 1, pp. 62-73, 2012.

A. Blazinskas, A. Misevicius, and A. Lenkevicius,
Modified Local Search Heuristics for the Symmetric Traveling Salesman Problem.
Information Technology and Control, Vol.42, No.3, pp. 218-230, 2013.

S. Bochkarev and S. L. Smith,
On Minimizing Turns in Robot Coverage Path Planning.
IEEE Conference on Automation Science and Engineering, 2016.

S. Bochkarev,
Minimizing Turns in Single and Multi Robot Coverage Path Planning.
Ph.D. thesis, University of Waterloo, 2017.

F. Bohnen, M. Buhl, and J, Deuse,
Systematic procedure for leveling of low volume and high mix production.
CIRP Journal of Manufacturing Science and Technology, Volume 6, Issue 1, pp. 53-58, 2013.

R. I. Bolaños,
Un algoritmo metaheurístico para la solución del problema de ruteo de vehículos con
múltiples depósitos y flota heterogénea.
Thesis, Universidad Tecnológica de Pereira, 2014.

R. I. Bolaños, J. W. Escobar, and M. G. Echeverri,
A metaheuristic algorithm for the multi-depot vehicle routing problem with
heterogeneous fleet.
International Journal of Industrial Engineering Computations, Vol. 9, pp. 461-478, 2018.

P. Bollweg, D. Hasanbegovic, H. Müller, and M. Stöneberg,
Surface-adaptive and Collision-avoiding Path Planning for Five-axis Milling.
Universität Dortmund, Forshungsberict Nr. 808, 2006.

M. Bolognini, L. Fagiano, and M. P. Limongelli,
A fault-tolerant automatic mission planner for a fleet of aerial vehicles.
Control Engineering Practice, Volume 135, 2023.

M. Bolognini and L. Fagiano,
A Scalable Hierarchical Path Planning technique for Autonomous Inspections
with multicopter drones.
European Control Conference, pp. 787-792, 2021.

M. Bolognini, L. Fagiano, and M. P. Limongelli,
An autonomous, multi-agent UAV platform for inspection of civil infrastructure.
Proceedings of the Internaltional Conference on Structural Health Mononitoron of
Intelligent Infrastructure, 2022.

T. Bonny and J. Henkel,
Using Lin-Kernighan algorithm for look-up table compression to improve code density.
Proceedings of the 16th ACM Great Lakes symposium on VLSI, pp. 259-265, 2006.

T. Bonny and J. Henkel,
Efficient code density through look-up table compression.
Proceedings of the conference on Design, automation and test in Europe, pp. 809-814, 2007.

T. Bonny and J. Henkel,
Instruction Re-encoding Facilitating Dense Embedded Code.
IEEE/ACM Proc. of Design, Automation and Test in Europe Conference, pp. 770-775, 2008.

T. Bonny and J. Henkel,
Huffman-based code compression techniques for embedded processors.
ACM Transactions on Design Automation of Electronic Systems, 15(4), Article 31, 2010.

G. Bono,
Deep multi-agent reinforcement learning for dynamic and stochastic vehicle routing problems.
Networking and Internet Architecture.
Ph.D thesis, Université de Lyon, 2020.

G. Bono, J. S. Dibangoye, O. Simonin, L. Matignon, and F. Pereyron,
Solving Multi-Agent Routing Problems Using Deep Attention Mechanisms. 
IEEE Transactions on Intelligent Transportation Systems, pp.1-10, 2020.

G. Bono, J. S. Dibangoye, O. Simonin, L. Matignon, and F. Pereyron,
Solving Multi-Agent Routing Problems Using Deep Attention Mechanisms.
IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 12, pp. 7804-7813, 2021.

U. Boryczka and Ł. Strąk,
Efficient DPSO Neighbourhood for Dynamic Traveling Salesman Problem.
Proceedings of the 5th International Conference on Computational Collective Intelligence,
pp. 721-730, 2016.

J. Bossek and H. Trautmann,
Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP
Solvers with Maximum Performance Difference.
Conference of the Italian Association for Artificial Intelligence, pp. 3-12, 2016.

J. Bossek and H. Trautmann,
Evolving Instances for Maximizing Performance Differences of State-of-the-Art
Inexact TSP Solvers.
International Conference on Learning and Intelligent Optimization, pp. 48-59, 2016.

J. Bossek, C. Grimme, S. Meisel, G. Rudolph, and H. Trautmann,
Local Search Effects in Bi-Objective Orienteering.
Proceedings of GECCO '18, pp. 585-592, 2018.

J. Bossek, P. Kerschke, A. Neumann, M. Wagner, F. Neumann, and H. Trautmann,
Evolving diverse TSP instances by means of novel and creative mutation operators.
Proceedings of FOGA, 2019.

J. Bossek, P. Kerschke, and H. Trautmann,
A multi-objective perspective on performance assessment and automated selection
of single-objective optimization algorithms.
Applied Soft Computing Journal, Vol. 88, 2020.

J. Bossek, P. Kerschke, and H. Trautmann,
Anytime Behavior of Inexact TSP Solvers and Prespectives for Automated Algorithm
Selection.
arXiv:2005.13489v1 [cs.AI], 2020.

J. Bossek and F. Neumann,
Exploring the Feature Space of TSP Instances Using Quality Diversity.
arXiv:2202.02077 [cs.NE], 2022.

A. Botros, B. Gilhuly, N. Wilde, A. Sadeghi, J. Alonso-Mora, and S. L. Smith,
Optimizing Task Waiting Times in Dynamic Vehicle Routing.
arXiv:2307.03984 [cs.RO eess.SY], 2023.

W. Bouarroudj, Z. Boufaida, and L. Bellatreche,
Named entity disambiguation in short texts over knowledge graphs.
Knowledge and Information Systems, 2022.

R. Boudreault and C.-G. Quimper,
Improved CP-Based Lagrangian Relaxation Approach with an Application to the TSP.
Proceedings of IJCAI-21, 2021.

S. Brown,
Coverage Path Planning and Room Segmentation in Indoor Environments using the
Constriction Decomposition Method.
M.Sc. thesis, University of Waterloo, 2017.

S. I. Brown, R. G. McGarvey, and J. A. Ventura,
Total flowtime and makespan for a no-wait m-machine flowshop with set-up times separated.
Journal of the Operational Research Society, Volume 55, Number 6, pp. 614-621, 2004.

V. Bui, and T. Mai,
Imitation Improvement Learning for Large-Scale Capacitated Vehicle Routing Problems. 
Proceedings of the International Conference on Automated Planning and Scheduling, 
33(1), pp. 551-559., 2023.

L. P. Buriol, França, and P. Moscato,
A New Memetic Algorithm for the Asymmetric Traveling Salesman Problem.
Journal of Heuristics, 10, pp. 483-506, 2004.

R. Bähnemann, N. Lawrance, J. J. Chung, M. Pantic, R. Siegwart, and J. Nieto,
Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling
Salesman Problem.
In: Ishigami G., Yoshida K. (eds) Field and Service Robotics, pp. 277-290, 2021.

L. P. Cáceres, F. Pagnozzi, A. Franzin, and T. Stützle,
Automatic configuration of GCC using irace.
IRIDIA - Technical Report Series, TR/IRIDIA/2017-008, 2017.

H. I. Calvete, C. Galé, and J. A. Iranzo,.
An efficient evolutionary algorithm for the ring star problem.
European Journal of Operational Research, Volume 231, Issue 1, pp. 22-33, 2013.

H. I. Calvete, C. Galé, and J. A. Iranzo,
MEALS: A Multiobjective Evolutionary Algorithm with Local Search for solving the
bi-objective ring star problem.
European Journal of Operational Research, Vol. 250, Issue 2, pp. 377-388, 2016.

Y. Cao, Z. Sun, and G. Sartoretti.
DAN: Decentralized Attention-based Neural Network for the MinMax Multiple
Traveling Salesman Problem.
arXiv:2109.04205v2 [cs.RO] , 2022.

Z. Cao, Z. Du, and J. Yang,
Topological Map-Based Autonomous Exploration in Large-Scale Scenes
for Unmanned Vehicles. 
Drones, 8(4): 124, 2024.

F. Carrabs, R. Cerulli, and A. Raiconi,
A reduction heuristic for the all-colors shortest path problem.
RAIRO Operations Research, Volume 55, 2021.

D. Carrara,
Graph-based Word Sense Disambiguation.
Bachelor thesis, University of Milan, 2018.

K. Castelino, R. D’Souza, and P. K. Wright,
Tool-path Optimization for Minimizing Airtime during Machining.
Journal of Manufacturing Systems, Volume 22, part 3, pp 173-180, 2003.

A. V. de Carvalho, M. C. Goldbarg, and E. F. G. Goldbarg,
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F. Imeson and S. L. Smith,
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ACM Trans. Graph., Vol. 39, No. 6, Article 192, 2020.

T. Zhu, X. Shi, X. Xu, and Jinde Cao,
An accelerated end-to-end method for solving routing problems.
Neural Networks, 2023.

Y. Zhu and S. Wang,
Efficient Aerial Data Collection With Cooperative Trajectory Planning for Large-Scale
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IEEE Transactions on Communications, vol. 70, no. 1, pp. 433-444, 2022.

Y. Zhu and S. Wang,
Data Collection in Wireless Sensor Networks: A Truck-Assisted Multi-UAV Method.
IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems,
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Y. Zhu and S. Wang,
Flying Path Optimization of Rechargeable UAV for Data Collection in
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IEEE Sensors Letters, vol. 7, no. 2, pp. 1-4, 2023.

Y. Zhu and S. Wang,
Joint Deployment and Trajectory Planning of Multiple UAVs for
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GLOBECOM, pp. 1854-1859, 2023.

Y. Zhou, W. Xu, Z.-H. Fu, and M. Zhou,
Multi-Neighborhood Simulated Annealing-Based Iterated Local Search for
Colored Traveling Salesman Problems.
IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 9,
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Y. Zhou, Y. Kou, and M. Zhou,
Bilevel Memetic Search Approach to the Soft-Clustered Vehicle Routing Problem.
Transportation Science, 2022.

T. Zhu, X. Shi, Xinli, X. Xu, and J. Cao, Jinde,
An Accelerated End-to-End Method for Solving Routing Problems.
Preprint, SAvailable at SRN, 2023.

Y. Zhu and S. Wang,
Flying Path Optimization of Rechargeable UAV for Data Collection
in Wireless Sensor Networks.
IEEE Applied Sensing Conference, 2023.

G. N. Zhukova, M. V. Ulyanov, and M. l. Fomichev,
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Business Inormatics, No. 3(45), pp. 20-28, 2018.

G. N. Zhukova, M. V. Ulyanov, and M. l. Fomichev,
A Hybrid Exact Algorithm for the Asymmetric Traveling Salesman Problem:
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L. Zikou, C. Papachristos, K. Alexis, and A. Tzes,
Inspection Operations Using an Aerial Robot Powered-over-Tether by a Ground Vehicle.
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Z. Zong, H. Wang, J. Wang, M. Zheng, and Y. Li,
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Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery
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