A branch-and-cut algorithm for the Edge Interdiction Clique Problem

Given a graph G and an interdiction budget k∈N, the Edge Interdiction Clique Problem (EICP) asks to find a subset of at most k edges to remove from G so that the size of the maximum clique, in the interdicted graph, is minimized. The EICP belongs to the family of interdiction problems with the aim of reducing the clique number of the graph. The EICP optimal solutions, called optimal interdiction policies, determine the subset of most vital edges of a graph which are crucial for preserving its clique number. We propose a new set-covering-based Integer Linear Programming (ILP) formulation for the EICP with an exponential number of constraints, called the clique-covering inequalities. We design a new branch-and-cut algorithm which is enhanced by a tailored separation procedure and by an effective heuristic initialization phase. Thanks to the new exact algorithm, we manage to solve the EICP in several sets of instances from the literature. Extensive tests show that the new exact algorithm greatly outperforms the state-of-the-art approaches for the EICP

Efficient Algorithms for Finding Maximum and Maximal Cliques and Their Applications

The problem of finding a maximum clique or enumerating all maximal cliques is very important and has been explored in several excellent survey papers. Here, we focus our attention on the step-by-step examination of a series of branch-and-bound depth-first search algorithms: Basics, MCQ, MCR, MCS, and MCT. Subsequently, as with the depth-first search as above, we present our algorithm, CLIQUES, for enumerating all maximal cliques. Finally, we describe some of the applications of the algorithms and their variants in bioinformatics, data mining, and other fields

Finding maximum k-cliques faster using lazy global domination

No abstract available

A Much Faster Algorithm for Finding a Maximum Clique

We present improvements to a branch-and-bound maximumclique-finding algorithm MCS (WALCOM 2010, LNCS 5942, pp. 191–203) that was shown to be fast. First, we employ an efficient approximation algorithm for finding a maximum clique. Second, we make use of appropriate sorting of vertices only near the root of the search tree. Third, we employ a lightened approximate coloring mainly near the leaves of the search tree. A new algorithm obtained from MCS with the above improvements is named MCT. It is shown that MCT is much faster than MCS by extensive computational experiments. In particular, MCT is shown to be faster than MCS for gen400 p0.9 75 and gen400 p0.9 65 by over 328,000 and 77,000 times, respectively

Benchmark Problems for Exhaustive Exact Maximum Clique Search Algorithms

There are well established widely used benchmark tests to assess the performance of practical exact clique search algorithms. In this paper a family of further benchmark problems is proposed mainly to test exhaustive clique search procedures

Replicable parallel branch and bound search

Combinatorial branch and bound searches are a common technique for solving global optimisation and decision problems. Their performance often depends on good search order heuristics, refined over decades of algorithms research. Parallel search necessarily deviates from the sequential search order, sometimes dramatically and unpredictably, e.g. by distributing work at random. This can disrupt effective search order heuristics and lead to unexpected and highly variable parallel performance. The variability makes it hard to reason about the parallel performance of combinatorial searches. This paper presents a generic parallel branch and bound skeleton, implemented in Haskell, with replicable parallel performance. The skeleton aims to preserve the search order heuristic by distributing work in an ordered fashion, closely following the sequential search order. We demonstrate the generality of the approach by applying the skeleton to 40 instances of three combinatorial problems: Maximum Clique, 0/1 Knapsack and Travelling Salesperson. The overheads of our Haskell skeleton are reasonable: giving slowdown factors of between 1.9 and 6.2 compared with a class-leading, dedicated, and highly optimised C++ Maximum Clique solver. We demonstrate scaling up to 200 cores of a Beowulf cluster, achieving speedups of 100x for several Maximum Clique instances. We demonstrate low variance of parallel performance across all instances of the three combinatorial problems and at all scales up to 200 cores, with median Relative Standard Deviation (RSD) below 2%. Parallel solvers that do not follow the sequential search order exhibit far higher variance, with median RSD exceeding 85% for Knapsack

Reducing hypergraph coloring to clique search

It is known that the legal coloring of the nodes of a given graph can be reduced to a clique search problem. This paper generalizes this result for hypergraphs. Namely, we will show how legal coloring of the nodes of a hypergraph can be reduced to clique search in a uniform hypergraph. Replacing ordinary graphs by hypergraphs extends the descriptive power of graph models. In addition searching cliques in uniform hypergraphs may improve the efficiency of computations. As an illustration we will apply the reformulation technique to a hypergraph coloring problem due to Voloshin

Optimization Methods for Cluster Analysis in Network-based Data Mining

This dissertation focuses on two optimization problems that arise in network-based data mining, concerning identification of basic community structures (clusters) in graphs: the maximum edge weight clique and maximum induced cluster subgraph problems. We propose a continuous quadratic formulation for the maximum edge weight clique problem, and establish the correspondence between its local optima and maximal cliques in the graph. Subsequently, we present a combinatorial branch-and-bound algorithm for this problem that takes advantage of a polynomial-time solvable nonconvex relaxation of the proposed formulation. We also introduce a linear-time-computable analytic upper bound on the clique number of a graph, as well as a new method of upper-bounding the maximum edge weight clique problem, which leads to another exact algorithm for this problem. For the maximum induced cluster subgraph problem, we present the results of a comprehensive polyhedral analysis. We derive several families of facet-defining valid inequalities for the IUC polytope associated with a graph. We also provide a complete description of this polytope for some special classes of graphs. We establish computational complexity of the separation problems for most of the considered families of valid inequalities, and explore the effectiveness of employing the corresponding cutting planes in an integer (linear) programming framework for the maximum induced cluster subgraph problem

Algoritmos para o problema da clique máxima : análise e comparação experimental

Orientador : Prof. Dr. Renato CarmoTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 28/09/2017Inclui referências : f. 107-113Resumo: O problema da Clique Máxima (CM) é um problema fundamental e há uma grande motivação pela busca de algoritmos tão eficientes quanto possível para resolvê-lo de forma exata. Como esperado para um problema NP-difícil, os melhores algoritmos com desempenho de pior caso conhecido tem custo de tempo exponencial. Por outro lado, resultados experimentais encontrados na literatura indicam que instâncias de tamanho considerável podem ser resolvidas usando algoritmos baseados na técnica de branch-and-bound. Com isso, observa-se uma distância entre os melhores resultados analíticos e os melhores resultados experimentais. Uma possível explicação para discrepância aparente entre teoria e prática foi encontrada pela análise de instâncias aleatórias. Diversos algoritmos de branch- and-bound para a solução exata do CM foram estudados, analisados e implementados. Com base nos resultados analíticos é proposta uma metodologia para comparação experimental de algoritmos, que tem como principal ponto positivo o fato de que algoritmos podem ser comparados independente de detalhes de implementação e execução. Vários algoritmos foram testados como prova de conceito. Também foram estudadas instâncias de pior caso para algoritmos de branch-and-bound que só utilizam coloração como limitante superior, resultando em um custo exponencial de tempo para estes algoritmos. Uma nova família de algoritmos foi desenvolvida, capaz de resolver tais instâncias em tempo polinomial. Recentemente, técnicas de resolvedores para problemas de satisfatibilidade têm sido aplicadas em algoritmos para CM. Tais técnicas dependem de uma redução entre os dois problemas, mas o significado em termos do grafo fica obscurecido nas descrições originais. Algumas técnicas foram estudadas e convertidas para uma descrição que não usa termos referentes aos problemas de satisfatibilidade. A implementação de vários algoritmos estudados foi disponibilizada em um repositório de acesso público. Palavras-chave: Solução exata. Branch-and-bound. Análise de algoritmos. Comparação experimental.Abstract: e Maximum Clique problem (CM) is a fundamental problem and there is a great motivation for the development of efficient exact algorithms to solve it. As expected for a NP-hard problem, the best algorithms where worst case analyses have been conducted present exponential running times. On the other hand, experimental results available in the literature show that instances of considerable size can be solved by branch and bound algorithms. Therefore, there is an apparent gap between the best theoretical results and the best experimental results. One possible explanation for this discrepancy between theory and practice was found through the analyses of random instances. Several exact branch and bound algorithm for CM were studied, analyzed and implemented. Based on these analytical results, a new methodology for the comparison of algorithms is proposed, where algorithms can be tested and compared regardless of implementation and execution details. Several algorithms were tested as a proof of concept. Worst case instances for some branch and bound algorithms were studied, namely algorithms that adopt only coloring-based bounding techniques to reduce the search space. These algorithms present exponential time cost for the studied instances. A new family of algorithms was developed, which is able to solve the mentioned instances in polinomial time. Recently, techniques from satisfiability solvers have been used in algorithms for CM. Such techniques depend on a reduction between the problems, and the original descriptions in terms of propositional calculus obscures their graph theoretic meaning. Some of these techniques were studied and converted to a description that uses only graph theory terminology. The implementation of several algorithms was made available in a public access repository. Keywords: Exact solution. Branch-and-bound. Analysis of algorithms. Experimental comparison