A Generator for Random Non-Binary Finite Constraint Satisfaction Problems
نویسندگان
چکیده
The paper describes an implementation of a generator of random instances of non-binary constraint satisfaction problems that meets a given set of specifications. This is a continuation of the work we started in [1]. 1 Description The program is designed to generate random instances of Constraint Satisfaction Problems (CSPs) that meet a set of specified parameters, such as the number of variables, domain size, constraint density, tightness. At the same time, it can generate any combination of binary, ternary, and/or quaternary constraints specifies as percentage of the total number of constraints in the problem. 2 Assumptions To realize this program, we make the following assumptions: 1. All variables have the same domains. 2. Any particular group of variables has only one constraint of a given arity. 3. All constraints have the same tightness. 4. All variables are equally likely to be connected by a constraint. 5. We guarantee that the resulting CSP is connected. 3 Parameters The input parameters are the following: • n: the number of variables • a: domain size. 1 • p: constraint probability. • p2: the percentage of binary constraints. • p3: the percentage of ternary constraints. • p4: the percentage of quaternary constraints. • t: tightness of a constraint, which is the ratio of the number of incompatible tuples over the number of all possible tuples. Given the input parameters, we compute internally a number of other parameters that we use to generate the CSP. • C is the total number of constraints, including binary, ternary and quaternary. • c2 is the number of binary constraints. • c3 is the number of ternary constraints • c4 is the number of quaternary constraints The relations between C , c2, c3, and c4 are as follows: C = c2 + c3 + c4 (1) C = (
منابع مشابه
Comparing evolutionary algorithms on binary constraint satisfaction problems
Constraint handling is not straightforward in evolutionary algorithms (ea) since the usual search operators, mutation and recombination, are ‘blind’ to constraints. Nevertheless, the issue is highly relevant, for many challenging problems involve constraints. Over the last decade numerous eas for solving constraint satisfaction problems (csp) have been introduced and studied on various problems...
متن کاملSharp thresholds for constraint satisfaction problems and homomorphisms
We determine under which conditions certain natural models of random constraint satisfaction problems have sharp thresholds of satisfiability. These models include graph and hypergraph homomorphism, the (d, k, t)-model, and binary constraint satisfaction problems with domain size 3.
متن کاملThe Satisfiability Threshold for Randomly Generated Binary Constraint Satisfaction Problems
We study two natural models of randomly generated constraint satisfaction problems. We determine how quickly the domain size must grow with n to ensure that these models are robust in the sense that they exhibit a non-trivial threshold of satisfiability, and we determine the asymptotic order of that threshold. We also provide resolution complexity lower bounds for these models. One of our resul...
متن کاملPOLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with ≤ and ≠
Nowadays, many real problems can be naturally modelled as Constraint Satisfaction Problems (CSPs). It is well known that any non-binary CSP can be transformed into an equivalent binary one, using some of the current techniques. However, this transformation may not be practical in problems with certain properties. Therefore, it is necessary to manage these non-binary constraints directly. In thi...
متن کاملPreprocessing Algorithms for non-binary Disjunctive Temporal Constraints Satisfaction Problems
Some constraint languages are more powerful than others because they allow us to express a larger collection of problems. More generally, the finite constraint satisfaction problem (CSP) with arbitrary constraints (nonbinary), is known to be NP-complete [9], whereas many families of restricted constraints have been identified like tractable subproblems [1][7]. We propose two preprocessing algor...
متن کامل