In the sequel we consider the job shop scheduling problem with uncertain durations represented as triangular fuzzy numbers. We propose a new neighbourhood structure for local search, based on a new definition of critical path for fuzzy durations. A theoretical analysis of the proposed structure shows that it improves a previous one from the literature. It also shows that feasibility and connect...

Using constraint-based local search, we effectively model and efficiently solve the problem of balancing the traffic demands on portions of the European airspace while ensuring that their capacity constraints are satisfied. The traffic demand of a portion of airspace is the hourly number of flights planned to enter it, and its capacity is the upper bound on this number under which air-traffic c...

We propose and study a technique to improve the performance of those local-search SAT solvers that proceed by executing a prespecified number of tries, each starting with an element of the space of all truth assignments and performing a prespecified number of local-search steps (flips). Based on the input theory T, our method first constructs a collection of its relaxations, that is, theories w...

Local search metaheuristics are a recognized means of solving hard combinatorial problems. Over the last couple of decades, significant advances have been made in terms of the formalization, applicability and performance of these methods. Key to the performance aspect is the increased availability of parallel hardware, which turns out to be largely exploitable by this class of procedures. As re...

In this paper, we investigate the complexity of computing locally optimal solutions for the local search problem MAXIMUM CONSTRAINT ASSIGNMENT (MCA). For our investigation, we use the framework of PLS, as defined in Johnson et al. [9]. In a nutshell, the MCA-problem is a local search version of weighted, generalized MAXSAT on constraints (functions mapping assignments to integers) over variable...

Stochastic local search solvers for SAT made a large progress with the introduction of probability distributions like the ones used by the SAT Competition 2011 winners Sparrow2010 and EagleUp. These solvers though used a relatively complex decision heuristic, where probability distributions played a marginal role. In this paper we analyze a pure and simple probability distribution based solver ...

In this paper we present a new heuristic solution method for two-dimensional nesting problems. It is based on a simple local search scheme in which the neighborhood is any horizontal or vertical translation of a given polygon from its current position. To escape local minima we apply the meta-heuristic method Guided Local Search. The strength of our solution method comes from a new algorithm wh...

Variable neighborhood search (VNS) [4, 5] is a metaheuristic for solving optimization problems based on a simple principle: systematic changes of neighborhoods within the search, both in the descent to local minima and in the escape from the valleys which contain them. VNS applications have been numerous and successful. Many extensions have been made, mainly to be able to solve large problem in...

Local search is currently one of the most used methods for finding solutions in real-life problems. It is usually considered when the research is interested in the final solution of the problem instead of the how the solution is reached. In this paper, the authors present an implementation of local search with Membrane Computing techniques applied to the N-queens problem as a case study. A CLIP...

In the context of microarray data analysis, biclustering aims to identify simultaneously a group of genes that are highly correlated across a group of experimental conditions. This paper presents a Biclustering Iterative Local Search (BILS) algorithm to the problem of biclustering of microarray data. The proposed algorithm is highlighted by the use of some original features including a new eval...