Empirical Studies of Heuristic Local Search for Constraint Solving

نویسندگان

  • Jin-Kao Hao
  • Raphaël Dorne
چکیده

Abs t rac t . The goal of this paper is twofold. First, we introduce a class of local search procedures for solving optimization and constraint problems. These procedures are based on various heuristics for choosing variables and values in order to examine a general neighborhood. Second, four combinations of heuristics are empirically evaluated by using the graph-coloring problem and a real world application the frequency assignment problem. The results are also compared with those obtained with other approaches including simulated annealing, Tabu search, constraint programming and heuristic graph coloring algorithms. Empirical evidence shows the benefits of this class of local search procedures for solving large and hard instances.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

DFS-Tree Based Heuristic Search

In constraint satisfaction, local search is an incomplete method for finding a solution to a problem. Solving a general constraint satisfaction problem (CSP) is known to be NP-complete; so that heuristic techniques are usually used. The main contribution of this work is twofold: (i) a technique for de-composing a CSP into a DFS-tree CSP structure; (ii) an heuristic search technique for solving ...

متن کامل

Solving Vehicle Routing Problems Using Constraint Programming and Metaheuristics

Constraint Programming typically uses the technique of depth-first branch and bound as the method of solving optimisation problems. Although this method can give the optimal solution, for large problems, the time needed to find the optimal can be prohibitive. This paper introduces a method for using iterative improvement techniques within a Constraint Programming framework, and applies this tec...

متن کامل

An E cient Heuristic-Based Evolutionary Algorithm for Solving Constraint Satisfaction Problems

GENET and EGENET are local search algorithms based on artiicial neural networks which have proved very successful in solving hard constraint satisfaction problems (CSPs). In this paper we describe a micro-genetic algorithm for solving CSPs which generalizes the (E)GENET approach. It is based on min-connict local search together with two methods for escaping local minima: population based learni...

متن کامل

Explorative anytime local search for distributed constraint optimization

Distributed Constraint Optimization Problems (DCOPs) are an elegant model for representing and solving many realistic combinatorial problems that are distributed by nature. DCOPs are NP-hard and therefore many recent studies consider incomplete algorithms for solving them. Distributed local search algorithms, in which agents in the system hold value assignments to their variables and iterativel...

متن کامل

A Local Search Approach to Modelling and Solving Interval Algebra Problems

Local search techniques have attracted considerable interest in the artificial intelligence community since the development of GSAT and the minconflicts heuristic for solving propositional satisfiability (SAT) problems and binary constraint satisfaction problems (CSPs) respectively. Newer techniques, such as the discrete Langrangian method (DLM), have significantly ∗The authors gratefully ackno...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1996