This paper presents stochastic tree search, an alternative method to local search. Stochastic tree search consists of the exploration of a search tree, making use of heuristics for guiding the choice of the next branch, and a combination of diving and randomized selection of the path for exploring the tree. Stochastic tree search efficiency relies on avoiding the repetition of the search on the...

We study the performance of stochastic local search algorithms for random instances of the K-satisfiability (K-SAT) problem. We present a stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a problem instance by never going upwards in energy. ChainSAT is a focused algorithm in the sense that it focuses on variables occurring in unsatisfied clauses. We show by ext...

In this paper, we address the problem of local search for the falsification of hybrid automata with affine dynamics. Namely, given a sequence of locations and a maximum simulation time, we return the trajectory that comes closest to the unsafe set. This problem is formulated as a differentiable optimization problem and solved. The purpose of developing such a local search method is to combine i...

Subset selection problems are relevant in many domains. Unfortunately, their combinatorial nature prohibits solving them optimally in most cases. Local search algorithms have been applied to subset selection with varying degrees of success. This work presents COMPSET, a general algorithm for subset selection that invokes an existing local search algorithm from a random subset and its complement...

In recent years, much attention has been devoted to the development of metaheuristics and local search algorithms for tackling stochastic combinatorial optimization problems. In this paper, we propose an effective local search algorithm that makes use of empirical estimation techniques for a class of stochastic combinatorial optimization problems. We illustrate our approach and assess its perfo...

Automated high school timetabling is a challenging task. This problem is a well known hard computational problem which has been of interest to practitioners as well as researchers. High schools need to timetable their regular activities once per year, or even more frequently. The exact solvers may fail to find a solution for a given instance of the problem. A selection hyper-heuristic can be de...

We present a nested local search algorithm to approximate several variants of metric two-stage stochastic facility location problems. These problems are generalizations of the well-studied metric uncapacitated facility location problem, taking uncertainties in demand values and costs into account. The proposed nested local search procedure uses three facility operations: adding, dropping, and s...

Planning by incomplete stochastic search ooers a promising alternative to classical, complete planning methods. The success of this approach is documented by recent performance results obtained by transforming planning tasks into propositional sat-issability problems and using existing eecient local search methods to solve them. On the other hand, we argue that these results can still be improv...

The Gradual Learning Algorithm (GLA) (Boersma and Hayes, 2001) can be seen as a stochastic local search method for learning Stochastic OT grammars. This paper tries to achieve the following goals: first, in response to the criticism in (Keller and Asudeh, 2002), we point out that the computational problem of learning stochastic grammars does have a general approximate solution (Lin, 2005). Seco...