MC-nets is a concise representation of the characteristic functions that exploits a set of rules to compute payoffs. Given a MC-nets instance, the problem of computing a payoff division in the least core, which is a g...
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ISBN:
(数字)9783319131917
ISBN:
(纸本)9783319131917;9783319131900
MC-nets is a concise representation of the characteristic functions that exploits a set of rules to compute payoffs. Given a MC-nets instance, the problem of computing a payoff division in the least core, which is a generalization of the core-non-emptiness problem that is known to be coNP-complete, is definitely a hard computational problem. In fact, to the best of our knowledge, no algorithm can actually compute such a payoff division for MC-nets instances with dozens of agents. We propose a new algorithm for this problem, that exploits the constraint generation technique to solve the linear programming problem that potentially has a huge number of constraints. Our experimental results are striking since, using 8 GB memory, our proposed algorithm can successfully compute a payoff division in the least core for the instances with up to 100 agents, but the naive algorithm fails due to a lack of memory for instances with 30 or more agents.
We improve an existing propagator for the context-free grammar constraint and demonstrate experimentally the practicality of the resulting propagator. the underlying technique could be applied to other existing propag...
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ISBN:
(纸本)9783642406263;9783642406270
We improve an existing propagator for the context-free grammar constraint and demonstrate experimentally the practicality of the resulting propagator. the underlying technique could be applied to other existing propagators for this constraint. We argue that constraintprogramming solvers are more suitable than existing solvers for verification tools that have to solve string constraints, as they have a rich tradition of constraints for membership in formal languages.
It is well known that the constraint satisfaction problem over general relational structures can be reduced in polynomial time to digraphs. We present a simple variant of such a reduction and use it to show that the a...
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ISBN:
(纸本)9783642406263;9783642406270
It is well known that the constraint satisfaction problem over general relational structures can be reduced in polynomial time to digraphs. We present a simple variant of such a reduction and use it to show that the algebraic dichotomy conjecture is equivalent to its restriction to digraphs and that the polynomial reduction can be made in logspace. We also show that our reduction preserves the bounded width property, i.e., solvability by local consistency methods. We discuss further algorithmic properties that are preserved and related open problems.
Gutierrez and Meseguer show how to enforce consistency in BnB-ADOPT(+) for distributed constraint optimization, but they consider unconditional deletions only. However, during search, more values can be pruned conditi...
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ISBN:
(纸本)9783642406263;9783642406270
Gutierrez and Meseguer show how to enforce consistency in BnB-ADOPT(+) for distributed constraint optimization, but they consider unconditional deletions only. However, during search, more values can be pruned conditionally according to variable instantiations that define subproblems. Enforcing consistency in these subproblems can cause further search space reduction. We introduce efficient methods to maintain soft arc consistencies in every subproblem during search, a non trivial task due to asynchronicity and induced overheads. Experimental results show substantial benefits on three different benchmarks.
Soft neighborhood substitutability (SNS) is a powerful technique to automatically detect and prune dominated solutions in combinatorial optimization. Recently, it has been shown in [26] that enforcing partial SNS (PSN...
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ISBN:
(纸本)9783642406263;9783642406270
Soft neighborhood substitutability (SNS) is a powerful technique to automatically detect and prune dominated solutions in combinatorial optimization. Recently, it has been shown in [26] that enforcing partial SNS (PSNSr) during search can be worthwhile in the context of Weighted constraint Satisfaction Problems (WCSP). However, for some problems, especially with large domains, PSNSr is still too costly to enforce due to its worst-case time complexity in O(ned(4)) for binary WCSP. We present a simplified dominance breaking constraint, called restricted dead-end elimination (DEEr), the worst-case time complexity of which is in O(ned(2)). Dead-end elimination was introduced in the context of computational biology as a preprocessing technique to reduce the search space [13, 14, 16, 17, 28, 30]. Our restriction involves testing only one pair of values per variable instead of all the pairs, withthe possibility to prune several values at the same time. We further improve the original dead-end elimination criterion, keeping the same time and space complexity as DEEr. Our results show that maintaining DEEr during a depth-first branch and bound (DFBB) search is often faster than maintaining PSNSr and always faster than or similar to DFBB alone.
Recent years have seen an increasing interest in the application of constraint solving techniques to test, verify and analyze software systems. A significant body of constraint-based techniques has been proposed and i...
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ISBN:
(纸本)9780769549934;9781479913244
Recent years have seen an increasing interest in the application of constraint solving techniques to test, verify and analyze software systems. A significant body of constraint-based techniques has been proposed and investigated in the context of test input generation, model-based testing, symbolic execution, static analysis, program verification, and many other areas. these techniques use or extend constraint solvers such as SAT and SMT solvers to reason about boolean, integer, real and floating-point data types, as well as complex data structures, control structures, method calls and other program features. the constraint systems that result from this work usually share many common features and are relevant to a variety of application domains. Following a first meeting held withthe principles and practice of constraintprogramming (cp) conference in 2006, and three subsequent meetings at the internationalconference on Software Testing, Verification and Validation (ICST) in 2010, 2011 and 2012, the aim of this paper is to bring together researchers and practitioners working in constraint-based software testing, verification and analysis, to investigate future developments in this research field.
We present an extension to indexicals to describe propagators for global constraints. the resulting language is compiled into actual propagators for different solvers, and is solver-independent. In addition, we show h...
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Our goal is to investigate the definition and application of strong consistency properties on the dual graphs of binary constraint Satisfaction Problems (CSPs). As a first step in that direction, we study the structur...
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Bin packing is a ubiquitous problem that arises in many practical applications. the motivation for the work presented here comes from the domain of data centre optimisation. In this paper we present a parameterisable ...
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Domains in Continuous constraintprogramming (cp) are generally represented with intervals whose n-ary Cartesian product (box) approximates the solution space. this paper proposes a new representation for continuous v...
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