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Advances in BDD reduction using Parallel Genetic Algorithms
"... Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other finite state systems, as well as other problems. Nevertheless, the size of the BDD r ..."
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Cited by 5 (1 self)
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Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other finite state systems, as well as other problems. Nevertheless, the size of the BDD representation of these functions is highly dependent on the order of the function arguments, also called variables, and to nd such good ordering is an NPComplete problem. Many heuristics have been proposed to solve this problem, as the depthfirst traversal algorithm, one of the best known techniques, and the genetic algorithm found in [6]. In this paper, we present a improvement to them, through a parallel genetic algorithm, and compare its experimental results with those obtained from an interleavingbased implementation of the depthfirst traversal algorithm, applying them to the ISCAS85 benchmark circuits.
Parallel strategies for GRASP with pathrelinking
, 2005
"... ABSTRACT. A Greedy Randomized Adaptive Search Procedure (GRASP) is a metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and a local search. Pathrelinking is an intensification strategy that explores trajectories that ..."
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Cited by 4 (2 self)
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ABSTRACT. A Greedy Randomized Adaptive Search Procedure (GRASP) is a metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and a local search. Pathrelinking is an intensification strategy that explores trajectories that connect high quality solutions. We analyze two parallel strategies for GRASP with pathrelinking and propose a criterion to predict parallel speedup based on experiments with a sequential implementation of the algorithm. Independent and cooperative parallel strategies are described and implemented for the 3index assignment problem and the jobshop scheduling problem. The computational results for independent parallel strategies are shown to qualitatively behave as predicted by the criterion. 1.
Variable Ordering of BDDs with Parallel Genetic Algorithms
"... Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other finite state systems, as well as other problems. Nevertheless, the size of the BDD re ..."
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Cited by 4 (4 self)
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Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other finite state systems, as well as other problems. Nevertheless, the size of the BDD representation of these functions is highly dependent on the order of the function arguments, also called variables, and to find such good ordering is a NPComplete problem. In this work we present an heuristic based on Parallel Genetic Algorithms to solve this problem together with experimental results.
Foundations of Stochastic Diffusion Search
, 2004
"... Stochastic Diffusion Search (sds) was introduced by Bishop (1989a) as an algorithm to solve pattern matching problems. It relies on many concurrent partial evaluations of candidate solutions by a population of agents and communication between those agents to locate the optimal match to a target patt ..."
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Cited by 3 (0 self)
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Stochastic Diffusion Search (sds) was introduced by Bishop (1989a) as an algorithm to solve pattern matching problems. It relies on many concurrent partial evaluations of candidate solutions by a population of agents and communication between those agents to locate the optimal match to a target pattern in a search space. In subsequent research, several variations on the original algorithmic formulation were proposed. It also became evident that its main principles – partial evaluation and communication between agents – can be employed to problems outside the pattern matching domain. The primary aim of this dissertation is to develop these expansive views further: sds is proposed as a metaheuristic, a generic heuristic procedure for solving problems through search. Furthermore, it is proposed as a challenge to the dominant metaphor in computer science: sequential computation. The thesis proceeds in a structured way by first considering all questions that can be asked about a heuristic procedure like sds: questions of a foundational nature, questions pertaining to mathematical analysis, questions about application domains and questions about physical implementation. It is to the foundational issues that most attention is devoted. Analogies with selective processes in natural and social systems are investigated, as well as analogies with other metaheuristic techniques from artificial intelligence. An attempt is made to categorise potential variants, and to establish what kind of problems sds would be the optimal problemsolving method for. The work aims to provide an expanded but structured understanding of sds, to give guidelines for future work, and to establish how progress in other scientific disciplines can be of use in the study of sds, and vice versa. Preface All sciences characterise the essential nature of the systems they study. These characterisations are invariably qualitative in nature, for they set the terms with which more detailed knowledge can be developed. A. Newell and H. Simon (Newell and Simon, 1976) Cybernetics is the science of defensible metaphors.
A cachebased parallel genetic algorithm for the BDD variable ordering problem
, 2000
"... Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other finite state systems, as well as other problems. Nevertheless, the size of the BDD repr ..."
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Cited by 3 (3 self)
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Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other finite state systems, as well as other problems. Nevertheless, the size of the BDD representation of these functions is highly dependent on the order of the function arguments, also called variables, and to find such good ordering is an NPComplete problem. Many heuristics have been proposed to solve this problem, as our Parallel Genetic Algorithm presented in [4], where we got excellent results in terms of parallelization. Now, we present a new version of our algorithm, this time with a cache system, together with experimental results.
PARALLEL GREEDY RANDOMIZED ADAPTIVE SEARCH PROCEDURES
, 2004
"... A GRASP (Greedy Randomized Adaptive Search Procedure) is a metaheuristic for producing goodquality solutions of combinatorial optimization problems. It is usually implemented with a construction procedure based on a greedy randomized algorithm followed by local search. In this Chapter, we survey p ..."
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Cited by 3 (1 self)
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A GRASP (Greedy Randomized Adaptive Search Procedure) is a metaheuristic for producing goodquality solutions of combinatorial optimization problems. It is usually implemented with a construction procedure based on a greedy randomized algorithm followed by local search. In this Chapter, we survey parallel implementations of GRASP. We describe simple strategies to implement independent parallel GRASP heuristics and more complex cooperative schemes using a pool of elite solutions to intensify the search process. Some applications of independent and cooperative parallelizations are presented in detail.
A distriuted and probabilistic concurrent constraint programming language
, 2005
"... Abstract. We present a version of the CCP paradigm, which is both distributed and probabilistic. We consider networks with a fixed number of nodes, each of them possessing a local and independent constraint store. While locally the computations evolve asynchronously, following the usual rules of (pr ..."
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Cited by 2 (1 self)
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Abstract. We present a version of the CCP paradigm, which is both distributed and probabilistic. We consider networks with a fixed number of nodes, each of them possessing a local and independent constraint store. While locally the computations evolve asynchronously, following the usual rules of (probabilistic) CCP, the communications among different nodes are synchronous. There are channels, and through them different objects can be exchanged: constraints, agents and channel themselves. In addition, all this activities are embedded in a probabilistic scheme based on a discrete model of time, both locally and globally. Finally we enhance the language with the capability of performing an automatic remote synchronization of variables belonging to different constraint stores. 1
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"... Constraintbased approaches to stochastic dynamics of biological systems Candidate: ..."
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Constraintbased approaches to stochastic dynamics of biological systems Candidate:
Universidade Federal do Rio Grande do Norte Departamento de Informa'tica e Matema'tica Aplicada
"... 1 Introduction Binary Decision Diagrams (BDDs) are a data structure with an associated set of handling algorithms that has been shown very useful to deal with propositional Boolean functions [2]. BDDs represent these functions by means of reduced directed acyclic graphs. Along the paths of this grap ..."
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1 Introduction Binary Decision Diagrams (BDDs) are a data structure with an associated set of handling algorithms that has been shown very useful to deal with propositional Boolean functions [2]. BDDs represent these functions by means of reduced directed acyclic graphs. Along the paths of this graph, variables should be found in a fixed order. One important attribute of this data structure is the canonical representation of functions for each given variable ordering. This allows the execution of generally expensive tests, like equivalence and satisfiability, at unitary cost[2]. One of the most powerful applications of BDDs has been symbolic model checking, employed in the formal verification of digital circuits and other finite state systems [16]. With BDDs, formal verification tools were able to handle finitestate systems with more than 1020 states[13].
MultiAgent Simulation of Protein Folding
 In Proceedings of MASBIOMED 2005
, 2005
"... A protein is identified by a finite sequence of amino acids, each of them chosen from a set of 20 elements. The Protein Structure Prediction Problem, fundamental for biological and pharmaceutical research, is the problem of predicting the 3D native conformation of a protein, when its sequence of ..."
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A protein is identified by a finite sequence of amino acids, each of them chosen from a set of 20 elements. The Protein Structure Prediction Problem, fundamental for biological and pharmaceutical research, is the problem of predicting the 3D native conformation of a protein, when its sequence of amino acids is known. All current mathematical models of the problem are affected by intrinsic computational limits, and by a disagreement on which is the most reliable energy function to be used.