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A General backtrack algorithm for the isomorphism problem of combinatorial objects

G. Butler, C.W.H. Lam
1985 Journal of symbolic computation  
An interface between the two parts is developed to provide a general backtrack algorithm for the isomorphism problem of combinatorial objects that incorporates the technique of branch-and-bound, and that  ...  Our aim is to present a practical algorithm for the isomorphism problem that can be easily adapted to any class of combinatorial objects .  ...  By this means, an algorithm for the isomorphism problem of a specific class of combinatorial objects can be quickly developed and implemented .  ... 
doi:10.1016/s0747-7171(85)80021-3 fatcat:5wj7ktrsz5g7nl3iwcpmezhl6e

About an Approach for Constructing Combinatorial Objects

Iliya Bouyukliev, Maya Hristova
2018 Cybernetics and Information Technologies  
The classification of combinatorial objects consists of two sub-problems – construction of objects with given properties and rejection of isomorphic objects.  ...  In this paper, we consider generation of combinatorial objects that are uniquely defined by a matrix. The method that we present is implemented by backtrack search.  ...  It requires the development of effective algorithms for constructing combinatorial objects.  ... 
doi:10.2478/cait-2018-0019 fatcat:bnulxq6h2bdoznbaxsil3uo3ta

FPGA Generators of Combinatorial Configurations in a Linear Array Model

Zbigniew Kokosinski, Pawel Halesiak
2008 2008 International Symposium on Parallel and Distributed Computing  
In this paper we describe hardware implementations of generators of combinatorial objects.  ...  For implementation several systolic algorithms were selected that generate combinatorial configurations in a linear array model.  ...  Acknowledgements The research was supported in part by a research grant number E-7/423/BW/2008 obtained from CUT by the first author.  ... 
doi:10.1109/ispdc.2008.48 dblp:conf/ispdc/KokosinskiH08 fatcat:t5td5bmp3jacnj33ozzzxukwfi

O(1) Time Algorithms for Combinatorial Generation by Tree Traversal

T. Takaoka
1999 Computer journal  
There are algorithms for generating combinatorial objects such as combinations, permutations and wellformed parenthesis strings in O(1) time per object in the worst case.  ...  To derive O(1) time algorithms for combinatorial generation systematically, we formalize the idea of combinatorial Gray code by a twisted lexico tree, which is obtained from the lexicographic tree for  ...  Acknowledgement The author is very grateful to anonymous referees whose careful review improved the quality of the paper to a great extent.  ... 
doi:10.1093/comjnl/42.5.400 fatcat:f7rbbff6rngjvkexkvei2bkyli

Method for Developing Combinatorial Generation Algorithms Based on AND/OR Trees and Its Application

Yuriy Shablya, Dmitry Kruchinin, Vladimir Kruchinin
2020 Mathematics  
The main purpose of our research is to derive and improve general methods for developing combinatorial generation algorithms.  ...  In this paper, we study the problem of developing new combinatorial generation algorithms.  ...  Acknowledgments: The authors would like to thank the referees for their helpful comments and suggestions. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math8060962 fatcat:36uu7e7gbraapoyn5ip65aqgd4

Random generation of trees and other combinatorial objects

Elena Barcucci, Alberto Del Lungo, Elisa Pergola
1999 Theoretical Computer Science  
In this paper, we present a general method for the random generation of some classes of combinatorial objects.  ...  Our basic idea is to translate EC0 method (Enumerating Combinatorial Objects) from a method for the enumeration of combinatorial objects into a random generation method.  ...  In Section 3, we describe the generic algorithm for the uniform random generation of combinatorial objects.  ... 
doi:10.1016/s0304-3975(98)00322-3 fatcat:r7ygnfbr2vdtncda54yglhva2u

The Art of Computer Programming, by D.E. Knuth

Brian Borchers
2006 Scientific Programming  
In Section 7.2.1.7, Knuth discusses the history of algorithms for generating combinatorial objects. The history of the subject goes back thousands of years.  ...  A second section gives a history of algorithms for generating combinatorial objects. This section includes many references to material in fascicles 2 and 3.  ... 
doi:10.1155/2006/281781 fatcat:qw2fjbbvhvgy3ow5afg2cobvfe

An Efficient Generic Algorithm for the Generation of Unlabelled Cycles [chapter]

Conrado Martínez, Xavier Molinero
2004 Mathematics and Computer Science III  
Given the generic nature of the algorithm, it is suitable for inclusion in combinatorial libraries and for rapid prototyping.  ...  In this paper, we combine two recent generation algorithms to obtain a new algorithm for the generation of unlabelled cycles.  ...  This is because the new algorithm for cycles operates rather differently of the other generation algorithms with which it should be integrated (the algorithm for multisets is prototypical in that respect  ... 
doi:10.1007/978-3-0348-7915-6_19 fatcat:hvxzbe3ksfc25j4yzne4hheh5y

Boltzmann samplers for first-order differential specifications

Olivier Bodini, Olivier Roussel, Michèle Soria
2012 Discrete Applied Mathematics  
In the framework of analytic combinatorics, Boltzmann models give rise to efficient algorithms for the random generation of combinatorial objects.  ...  is allowed on the size of the generated object.  ...  Acknowledgments The authors are very grateful to the referees for their perceptive and encouraging comments.  ... 
doi:10.1016/j.dam.2012.05.022 fatcat:2iw5thfgtvfj7hazjqbfkcjf5a

Handling constraints in combinatorial interaction testing in the presence of multi objective particle swarm and multithreading

Bestoun S. Ahmed, Luca M. Gambardella, Wasif Afzal, Kamal Z. Zamli
2017 Information and Software Technology  
Objective: This paper presents a new strategy, to construct combinatorial interaction test suites in the presence of constraints. Method: The design and algorithms are provided in detail.  ...  Conclusion: The proposed strategy can form a new way for constructing of constrained combinatorial interaction test suites. The strategy can form a new and effective base for future implementations.  ...  Objective: This paper presents a new strategy, to construct combinatorial interaction test suites in the presence of constraints. Method: The design and algorithms are provided in detail.  ... 
doi:10.1016/j.infsof.2017.02.004 fatcat:xv6dm2psxvhcbpubd3bb5qvqzq

A Novel Particle Swarm Optimization Algorithm for Multi-Objective Combinatorial Optimization Problem

Rahul Roy, Satchidananda Dehuri, Sung Bae Cho
2011 International Journal of Applied Metaheuristic Computing  
The experimental results confirmed the better performance of combinatorial particle swarm optimization algorithm.  ...  The performance of the algorithm is compared with other evolutionary strategy like SPEA and NSGA-II on pseudo-Boolean discrete problems and multi-objective 0/1 knapsack problem.  ...  Zitzler et al. (1999) implemented some of the state-ofthe-art combinatorial optimization problems with multi-objective genetic algorithm.  ... 
doi:10.4018/jamc.2011100104 fatcat:2nkpqhgtw5a5hdtojiqql3fen4

Efficient iteration in admissible combinatorial classes

Conrado Martínez, Xavier Molinero
2005 Theoretical Computer Science  
developed by the authors for the unranking of combinatorial objects.  ...  The novel approach of the work presented here is to provide efficient generic algorithms, where the input is not just the size n of the objects to be generated but a finite specification of the combinatorial  ...  Acknowledgements We thank the comments and suggestions made by the referees of the preliminary version of this paper.  ... 
doi:10.1016/j.tcs.2005.08.028 fatcat:rs627tvvqjdd5hnbtq2t2idiju

ECO Method and the Exhaustive Generation of Convex Polyominoes [chapter]

Alberto Del Lungo, Andrea Frosini, Simone Rinaldi
2003 Lecture Notes in Computer Science  
ECO is a method for the enumeration of classes of combinatorial objects based on recursive constructions of such classes.  ...  In this paper we use the ECO method and the concept of succession rule to develop an algorithm for the exhaustive generation of convex polyominoes.  ...  In the context of generating combinatorial objects, the primary performance goal is that the amount of computation is proportional to the number of generated objects.  ... 
doi:10.1007/3-540-45066-1_10 fatcat:5jyxfnipjrbjvbrkrbfa2eb55q

Multiobjective combinatorial optimization for performance evaluation by a meta-heuristic satisficing tradeoff method [chapter]

Hiroyuki Tamura, Tomohiro Shibata, Itsuo Hatono
1999 Global Production Management  
Usually, a conventional satisficing tradeoff method needs to solve a complex min-max problem in each iteration of the algorithm for a given aspiration level of each objective function.  ...  Firstly, Pareto optimal solutions (individuals) are generated by using a genetic algorithm with family elitist concept for a muItiobjective combinatorial optimization problem.  ...  Firstly, Pareto optimal solutions (individuals) are generated by using a genetic algorithm (Goldberg, 1989) with family elitist concept (Bedarahally, et al., 1996) for a multi objective combinatorial  ... 
doi:10.1007/978-0-387-35569-6_60 fatcat:d5abt5b6rjfcjke33xnd26aguy

A Novel, Evolutionary, Simulated Annealing inspired Algorithm for the Multi-Objective Optimization of Combinatorial Problems

Elias D. Nino, Carlos J. Ardila, Anangelica Chinchilla
2012 Procedia Computer Science  
This paper states a novel hybrid-metaheuristic based on deterministic swapping, evolutionary algorithms and simulated annealing inspired algorithms for the multi-objective optimization of combinatorial  ...  Unlike MODS, EMSA works using a search direction given by the assignation of weights to each objective function of the combinatorial problem to optimize.  ...  EMSA is defined as a hybrid metaheuristic based on Genetic Algorithms, Simulated Annealing and Deterministic Swapping [9] for the multi-objective optimization of combinatorial problems.  ... 
doi:10.1016/j.procs.2012.04.218 fatcat:z3ljy2nvlfeo7nqwdeajkojkhe
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