35,953 research outputs found
Dagstuhl Reports : Volume 1, Issue 2, February 2011
Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-HĂŒbner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro PezzĂ©, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn
Clustering of Local Optima in Combinatorial Fitness Landscapes
Using the recently proposed model of combinatorial landscapes: local optima
networks, we study the distribution of local optima in two classes of instances
of the quadratic assignment problem. Our results indicate that the two problem
instance classes give rise to very different configuration spaces. For the
so-called real-like class, the optima networks possess a clear modular
structure, while the networks belonging to the class of random uniform
instances are less well partitionable into clusters. We briefly discuss the
consequences of the findings for heuristically searching the corresponding
problem spaces.Comment: Learning and Intelligent OptimizatioN Conference (LION 5), Rome :
Italy (2011
Solving the undirected feedback vertex set problem by local search
An undirected graph consists of a set of vertices and a set of undirected
edges between vertices. Such a graph may contain an abundant number of cycles,
then a feedback vertex set (FVS) is a set of vertices intersecting with each of
these cycles. Constructing a FVS of cardinality approaching the global minimum
value is a optimization problem in the nondeterministic polynomial-complete
complexity class, therefore it might be extremely difficult for some large
graph instances. In this paper we develop a simulated annealing local search
algorithm for the undirected FVS problem. By defining an order for the vertices
outside the FVS, we replace the global cycle constraints by a set of local
vertex constraints on this order. Under these local constraints the cardinality
of the focal FVS is then gradually reduced by the simulated annealing dynamical
process. We test this heuristic algorithm on large instances of Er\"odos-Renyi
random graph and regular random graph, and find that this algorithm is
comparable in performance to the belief propagation-guided decimation
algorithm.Comment: 6 page
Recommended from our members
Developments in linear and integer programming
In this review we describe recent developments in linear and integer (linear) programming. For over 50 years Operational Research practitioners have made use of linear optimisation models to aid decision making and over this period the size of problems that can be solved has increased dramatically, the time required to solve problems has decreased substantially and the flexibility of modelling and solving systems has increased steadily. Large models are no longer confined to large computers, and the flexibility of optimisation systems embedded in other decision support tools has made on-line decision making using linear programming a reality (and using integer programming a possibility). The review focuses on recent developments in algorithms, software and applications and investigates some connections between linear optimisation and other technologies
- âŠ