Forward-chaining heuristic search is a well-established and popular paradigm for domain-independent planning. Its effectiveness relies on the heuristic information provided by a state evaluator, and the search algorithm used with this in order to solve the problem. This paper presents a new stochastic local-search algorithm for forward-chaining planning. The algorithm is used as the basis of a ...

Algorithms based on local search are popular for solving many optimization problems including the maximum satisfiability problem (MAXSAT). With regard to MAXSAT, the state of the art in performance for universal (i.e. non specialized solvers) seems to be variants of Simulated Annealing (SA) and MaxWalkSat (MWS), stochastic local search methods. Local search methods are conceptually simple, and ...

Iterated local search is a stochastic local search (SLS) method that combines a perturbation step with an embedded local search algorithm. In this article, we propose a new way of hybridizing iterated local search. It consists in using an iterated local search as the embedded local search algorithm inside another iterated local search. This nesting of local searches and iterated local searches ...

This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, con...

In this paper, statistical counting is introduced in the context of stochastic local search. From a sample of trajectories by independent local search computations, it is shown that interesting statistical information can be actually extracted about the search space, most notably an unbiased estimate of the number of solutions. Computational results for random #SAT instances are provided.