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A Study of Breakout Local Search for the Minimum Sum Coloring Problem
[chapter]
2012
Lecture Notes in Computer Science
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Résumé en anglais Given an undirected graph G = (V,E), the minimum sum coloring problem (MSCP) is to find a legal assignment of colors (represented by natural numbers) to each vertex of G such that the ...
BLS explores the search space by a joint use of local search and adaptive perturbation strategies. ...
doi:10.1007/978-3-642-34859-4_13
fatcat:kjxokib6z5ctngd2sjbtg6zj7u
Algorithms for the minimum sum coloring problem: a review
2016
Artificial Intelligence Review
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The Minimum Sum Coloring Problem (MSCP) is a variant of the well-known vertex coloring problem which has a number of AI related applications. ...
The purpose of this review is to provide a comprehensive inspection of the most recent and representative MSCP algorithms. ...
The minimum sum coloring problem (MSCP) is a variant of the GCP and aims to determine a proper k-coloring while minimizing the sum of the colors assigned to the vertices. ...
doi:10.1007/s10462-016-9485-7
fatcat:i7xxirvrwzetzcrbh6bfvlu6pq
Privacy for the Distributed Stochastic Algorithm with Breakouts
2020
International Symposium on Artificial Intelligence and Mathematics
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In this paper, we focus on privacy issues when solving Distributed Constraint Optimization Problems (DCOPs) using a local search approach. ...
Privacy has traditionally been a major motivation of distributed problem solving. ...
A privacy domain cost is generated for each value, with mean = 10 and std. dev. = 10. WGC is a variant of weighted random coloring problem over n = 200 variables with d = 30 colors. ...
dblp:conf/isaim/VionMPS20
fatcat:npyks6wq35blrn2nzllin6si6m
Breakout Local Search for the Travelling Salesman Problem
2018
Computing and informatics
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This paper presents a resolution of the TSP using the breakout local search metaheuristic algorithm (BLS), which is based on the iterated local search (ILS) framework and improves it by introducing some ...
The travelling salesman problem (TSP), a famous NP-hard combinatorial optimisation problem (COP), consists of finding a minimum length tour that visits n cities exactly once and comes back to the starting ...
Since then, it has been used for solving some COP, such as the minimum sum coloring problem [4] , maximum clique problems [5] , quadratic assignment problem [7] and max-cut problem [6] and has given ...
doi:10.4149/cai_2018_3_656
fatcat:q5qetbwy5vcjbhpvxzgatbyptu
Explorative anytime local search for distributed constraint optimization
2014
Artificial Intelligence
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A general framework that enhances distributed local search algorithms for DCOPs with the anytime property is proposed. ...
It reveals the advantage of the use of the proposed heuristics in the anytime framework over state-of-the-art local search algorithms. 1 ...
We use the term step for a synchronous iteration of a local search algorithm. ...
doi:10.1016/j.artint.2014.03.002
fatcat:rccwfkidmzendnsddnbu77zrfe
A Memetic Algorithm Based on Breakout Local Search for the Generalized Travelling Salesman Problem
[article]
2019
arXiv
pre-print
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We propose in this paper a new memetic algorithm based on the well-known Breakout Local Search (BLS) metaheuristic to provide good solutions for GTSP instances. ...
The Travelling Salesman Problem (TSP) is one of the most popular Combinatorial Optimization Problem. ...
2013c) and Minimum Sum Coloring Problem (Benlic and Hao 2012) , and has given very good results. ...
arXiv:1911.01966v1
fatcat:2k7jbhmxyjfonbiaaezkx7m7zi
Distributed partial constraint satisfaction problem
[chapter]
1997
Lecture Notes in Computer Science
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This paper provides the Distributed Partial Constraint Satisfaction Problem (DPCSP) as a new framework for dealing with over-constrained situations. ...
Many problems in multi-agent systems can be described as distributed Constraint Satisfaction Problems (distributed CSPs), where the goal is to nd a set of assignments to variables that satis es all constraints ...
We have also presented the synchronous branch and bound and the iterative distributed breakout for solving distributed maximal constraint satisfaction problems, which belong to a very important class of ...
doi:10.1007/bfb0017442
fatcat:ipnnmyy5abhnloznmkjtsxhfry
Distributed stochastic search and distributed breakout: properties, comparison and applications to constraint optimization problems in sensor networks
2005
Artificial Intelligence
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To meet these requirements, we study two existing DisCSP algorithms, distributed stochastic search algorithm (DSA) and distributed breakout algorithm (DBA), for solving DisCOPs and the distributed scheduling ...
Therefore, DSA is the algorithm of choice for our distributed scheduling problems and other distributed problems of similar properties. ...
The views and conclusions herein are those of the author and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the US Government ...
doi:10.1016/j.artint.2004.10.004
fatcat:acqzmdyxsjg2ncsahub4igz57e
An iterated local search algorithm for the minimum differential dispersion problem
[article]
2016
arXiv
pre-print
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the maximum sum and the minimum sum of the inter-element distances between any two chosen elements is minimized. ...
Given a set of n elements separated by a pairwise distance matrix, the minimum differential dispersion problem (Min-Diff DP) aims to identify a subset of m elements (m < n) such that the difference between ...
Breakout local search Three-phase search minimum sum coloring problem [1] quadratic minimum spanning tree problem [15] quadratic assignment problem [2] maximally diverse grouping problem [23] maximum ...
arXiv:1608.04217v1
fatcat:pv5x7h4dprhmdpawrbnfo3ajzi
A Column Generation-Based Lower Bound for the Minimum Sum Coloring Problem
2020
IEEE Access
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The objective of this paper is to derive a tight and efficient lower bound for the minimum sum coloring problem. ...
This NP-hard problem is a variant of the classical graph coloring problem where the objective is to minimize the sum of the colors. ...
These include the Tabu Search algorithm of Bouziri and Jouini [20] , the Multi-Neighbourhood search of Helmar and Chiarandini [21] , the Breakout Local Search algorithm of Benlic and Hao [22] , the ...
doi:10.1109/access.2020.2973122
fatcat:hv4vqpougbd5xjkqoxekqgc5ua
A Dynamic Clause Specific Initial Weight Assignment for Solving Satisfiability Problems Using Local Search
2021
Algorithms
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For decades, the use of weights has proven its superior ability to improve dynamic local search weighting algorithms' overall performance. ...
To examine the efficacy of the dynamic initial weight assignment, we conducted an extensive study of our new technique on many problems. ...
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data. ...
doi:10.3390/a14010012
fatcat:7ymjof44mrctlfq7hisl3sy2z4
Distributed Bayesian optimization of deep reinforcement learning algorithms
2020
Journal of Parallel and Distributed Computing
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Previously he studied Statistics at the University of Tennessee. ...
Modelfree approaches, on the other hand, are often simpler to implement but ignore the underlying structure of the problem we care about [19] . 2 J o u r n a l P r e -p r o o f Journal Pre-proof In this ...
The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide ...
doi:10.1016/j.jpdc.2019.07.008
fatcat:gwibvufibjhwjojaiqa7pj2xde
Theory of Evolutionary Algorithms (Dagstuhl Seminar 13271)
2013
Dagstuhl Reports
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Topics intensively discussed include a complexity theory for randomized search heuristics, evolutionary computation in noisy settings, the drift analysis technique, and parallel evolutionary computation ...
This seminar, now in its 7th edition, is the main meeting point of the highly active theory of randomized search heuristics subcommunities in Australia, Asia, North America and Europe. ...
Overview The EMO breakout session took place in the afternoon (4pm-6pm) of the second day of the Most of the topics discussed during the breakout session originated from theoretical studies by some of ...
doi:10.4230/dagrep.3.7.1
dblp:journals/dagstuhl-reports/DoerrHSW13
fatcat:bvetvtijcrchzifaxvoliosmly
Reactive Search Optimization: Learning While Optimizing
[chapter]
2010
International Series in Operations Research and Management Science
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The final purpose of Reactive Search Optimization (RSO) is to simplify the life for the final user of optimization. ...
Reactive Search Optimization has to do with learning for optimizing, with the insertion of a machine learning component into a solution process so that algorithm selection, adaptation, integration, are ...
The problem is as follows: Given a graph G with a color (label) assigned to each edge one looks for a spanning tree of G with the minimum number of different colors. ...
doi:10.1007/978-1-4419-1665-5_18
fatcat:vimnftpcvrfw7cresqaddwhp64
Quantifying the heterogeneity of the tectonic stress field using borehole data
2017
Journal of Geophysical Research - Solid Earth
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We find that the standard deviation in these boreholes strongly depends on the interval length analyzed, generally increasing up to a wellbore log length of about 600 m and constant for longer intervals ...
However, observational evidence for such scaling of the stress field heterogeneity is scarce. ...
Acknowledgments The World Stress Map project is acknowledged for their long-term effort of collecting data and providing it to the community. ...
doi:10.1002/2017jb014370
fatcat:zoxkgjj4tbhrrffszftrlerb4u
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