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Stochastic runtime analysis of a Cross-Entropy algorithm for traveling salesman problems

Zijun Wu, Rolf H. Möhring, Jianhui Lai
2018 Theoretical Computer Science  
This article analyzes the stochastic runtime of a Cross-Entropy Algorithm on two classes of traveling salesman problems.  ...  When the n vertices span a convex polygon, we obtain a stochastic runtime of O(n^3m^5+ϵ) with the vertex-based random solution generation, and a stochastic runtime of O(n^2m^5+ϵ) for the edge-based random  ...  The present article continues the stochastic runtime analysis of [32] , but now in combinatorial optimization with a study of CE on the traveling salesman problem (TSP).  ... 
doi:10.1016/j.tcs.2017.10.012 fatcat:qqwdyo4b3fg2jgoqtsvbmj7rse

Information theory inspired optimization algorithm for efficient service orchestration in distributed systems

Matheus Sant'Ana Lima, Seyedali Mirjalili
2021 PLoS ONE  
This network routing challenge can be modeled as a variation of the Travelling Salesman Problem (TSP).  ...  The quality of the results proves the flexibility of the proposed algorithm for problems with different complexities without relying in nature-inspired models such as Genetic Algorithms, Ant Colony, Cross  ...  This strategy allows us to map instances of the Hamiltonian circle problem to a decision version of the Traveling Salesman Problem and can be described as a decision problem to determine if exists a Hamiltonian  ... 
doi:10.1371/journal.pone.0242285 pmid:33395689 fatcat:suambxwnhfdrjaujxfjsbhkljy

Understanding the empirical hardness ofNP-complete problems

Kevin Leyton-Brown, Holger H. Hoos, Frank Hutter, Lin Xu
2014 Communications of the ACM  
traveling salesman problem), distributions of problem instances (we have considered dozens), solvers (again, dozens).  ...  More specifically, this article surveys over a decade of research 1 showing how to build empirical hardness models (EHMs) that, given a new problem instance, estimate the runtime of an algorithm in low-order  ...  , a standard encoding for problems with both discrete and continuous variables) [14, 19, 21] , and the traveling salesman problem (TSP) [21] .  ... 
doi:10.1145/2594413.2594424 fatcat:t2chnugwqrg3rcsa64yynxkftq

A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization [article]

Benjamin Doerr, Frank Neumann
2021 arXiv   pre-print
stochastic and dynamic problems.  ...  It discusses fine-grained models of runtime analysis of evolutionary algorithms, highlights recent theoretical insights on parameter tuning and parameter control, and summarizes the latest advances for  ...  Acknowledgements Frank Neumann has been support by the Alexander von Humboldt Foundation through a Humboldt Fellowship for Experienced Researchers and by the Australian Research Council through grant FT200100536  ... 
arXiv:2006.16709v3 fatcat:cm23qxphufdpvntoilo5idsioa

Cross-Entropy-Based Replay of Concurrent Programs [chapter]

Hana Chockler, Eitan Farchi, Benny Godlin, Sergey Novikov
2009 Lecture Notes in Computer Science  
Our approach is based on a novel application of the cross-entropy method, and it does not require any logical analysis of dependencies among concurrent events.  ...  Replay is an important technique in program analysis, allowing to reproduce bugs, to track changes, and to repeat executions for better understanding of the results.  ...  This setting matches, for example, the definitions of the traveling salesman problem and the Hamiltonian path problem in the context of CE method.  ... 
doi:10.1007/978-3-642-00593-0_14 fatcat:nrg42kbukjfkbprf7q7w2vafnm

Online planning for multi-robot active perception with self-organising maps

Graeme Best, Jan Faigl, Robert Fitch
2017 Autonomous Robots  
We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks.  ...  The algorithm has a runtime complexity that is polynomial in the number of nodes to be observed and the magnitude of the relative weighting of rewards.  ...  Analysis This section provides a theoretical analysis of the algorithm's runtime complexity and convergence, and then empirical analysis of the behaviour of the algorithm for various random environments  ... 
doi:10.1007/s10514-017-9691-4 fatcat:qnjkk2pgi5byff4xr7ac4dtdre

Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection [chapter]

Lars Kotthoff, Pascal Kerschke, Holger Hoos, Heike Trautmann
2015 Lecture Notes in Computer Science  
We investigate per-instance algorithm selection techniques for solving the Travelling Salesman Problem (TSP), based on the two state-of-the-art inexact TSP solvers, LKH and EAX.  ...  Our comprehensive experiments demonstrate that the solvers exhibit complementary performance across a diverse set of instances, and the potential for improving the state of the art by selecting between  ...  Acknowledgements We thank Thomas Stützle for letting us use the restart version of LKH 1.3 he implemented in the context of a different project and for helpful comments on earlier versions of this work  ... 
doi:10.1007/978-3-319-19084-6_18 fatcat:2ikshpkwa5aalmgyw2mfapqjsu

Vacation Model [chapter]

2013 Encyclopedia of Operations Research and Management Science  
A vector n-space is a set of vectors or points, each with n components, and rules for vector addition and multiplication by real numbers. Euclidean 3-space is a vector space.  ...  Traveling Salesman Problem The traveling salesman problem is the one vehicle point-to-point vehicle routing problem.  ...  The route in Fig. 1 represents a solution to a symmetric or undirected traveling salesman problem since the travel time between each pair of locations does not depend on the direction of travel.  ... 
doi:10.1007/978-1-4419-1153-7_200894 fatcat:zm5qf6pzmzbepkc55xmzunolhq

The Stochastic Replica Approach to Machine Learning: Stability and Parameter Optimization [article]

Patrick Chao, Tahereh Mazaheri, Bo Sun, Nicholas B. Weingartner and Zohar Nussinov
2018 arXiv   pre-print
We introduce a statistical physics inspired supervised machine learning algorithm for classification and regression problems.  ...  It has been shown to consistently exhibit high accuracy and readily allow for optimization of parameters, while simultaneously avoiding pitfalls of existing algorithms such as those associated with class  ...  [18, 19] , and for examining instances of the Traveling Salesman Problem [20] .  ... 
arXiv:1708.05715v3 fatcat:pf2lkcapbbbe5mxuzlsq2ovrwy

Learning-Based Approaches for Graph Problems: A Survey [article]

Kai Siong Yow, Siqiang Luo
2022 arXiv   pre-print
Most of these problems are typically addressed by exact algorithms, approximate algorithms and heuristics. There are however some drawback for each of these methods.  ...  Some famous examples include graph colouring, travelling salesman problem and subgraph isomorphism.  ...  Travelling Salesman Problem The travelling salesman problem (TSP) [88] is a famous combinatorial optimisation problem, which can be generalised to the vehicle routing problem.  ... 
arXiv:2204.01057v2 fatcat:6oinpd56njcu5ait43327r6ege

A Dynamic Algorithm for the Longest Common Subsequence Problem using Ant Colony Optimization Technique [article]

Arindam Chaudhuri
2013 arXiv   pre-print
We present a dynamic algorithm for solving the Longest Common Subsequence Problem using Ant Colony Optimization Technique.  ...  To the best of our knowledge, this is the first Ant Colony Optimization Algorithm for Longest Common Subsequence Problem.  ...  Acknowledgements We wish to thank all anonymous referees for their many useful comments. I dedicate this paper to the memory of my beloved father Bimal Krishna Chaudhuri.  ... 
arXiv:1307.1905v1 fatcat:hgoxcwe735euhchpgygbrosuee

A Literature Survey on Offline Automatic Algorithm Configuration

Yasemin Eryoldaş, Alptekin Durmuşoglu
2022 Applied Sciences  
Although there is very wide literature about algorithm configuration problems, a detailed survey analysis has not been conducted yet to the best of our knowledge.  ...  After explaining the logic of these methods, we also argued about their main advantages and disadvantages to help researchers or practitioners select the best possible method for their specific problem  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12136316 fatcat:gvv66r55xvcjbjvf4re5wlacvu

Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: A comparison of meta-features

Jorge Kanda, Andre de Carvalho, Eduardo Hruschka, Carlos Soares, Pavel Brazdil
2016 Neurocomputing  
The Traveling Salesman Problem (TSP) is one of the most studied optimization problems. Various metaheuristics (MHs) have been proposed and investigated on many instances of this problem.  ...  However, this is a very difficult task. We address this task by using a meta-learning approach based on label ranking algorithms.  ...  This work was also partially supported by FCT project "Evolutionary algorithms for Decision Problems in Management Science" (PTDC/EGE-GES/099741/2008); by projects ("NORTE-07-0124-FEDER-000057") and SML  ... 
doi:10.1016/j.neucom.2016.04.027 fatcat:ngngx4xxr5eepapnky4nffmlju

Ant colony optimization theory: A survey

Marco Dorigo, Christian Blum
2005 Theoretical Computer Science  
Ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems, finds itself currently at this point of its life cycle.  ...  Research on a new metaheuristic for optimization is often initially focused on proof-of-concept applications.  ...  Acknowledgements We wish to thank Mauro Birattari, Nicolas Meuleau, Michael Sampels, Thomas Stützle, and Mark Zlochin for the time they spent with us discussing subjects strictly related to this  ... 
doi:10.1016/j.tcs.2005.05.020 fatcat:iheajykvhvaqhnpxigdxlbmo6y

Introduction to MAchine Learning & Knowledge Extraction (MAKE)

Andreas Holzinger
2017 Machine Learning and Knowledge Extraction  
This requires a concerted international effort without boundaries, supporting collaborative, cross-domain, interdisciplinary and transdisciplinary work of experts from seven sections, ranging from data  ...  The goal is to provide an incomplete, personally biased, but consistent introduction into the concepts of MAKE and a brief overview of some selected topics to stimulate future research in the international  ...  A recent experimental work [40] demonstrates the usefulness on the Traveling Salesman Problem (TSP), which appears in a number of practical problems, e.g., the native folded three-dimensional conformation  ... 
doi:10.3390/make1010001 dblp:journals/make/Holzinger19 fatcat:3a2s7s5nzrdhjof2e6ujkzyofu
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