In this paper we describe a stochastic local search (SLS) procedure for finding satisfying models of satisfiable propositional formulae. This new algorithm, gNovelty, draws on the features of two other WalkSAT family algorithms: R+AdaptNovelty and GWSAT, while also successfully employing a dynamic local search (DLS) clause weighting heuristic to further improve performance. gNovelty was a Gold ...

This paper addresses the linear ordering problem, which has been solved using different metaheuristics approaches. These algorithms have the common problem of finding a proper balance of the intensification and diversification processes; in this work we propose an iterated local search in which it is incorporated a Becker heuristic strategy for constructing the initial solution, and a search st...

Pareto Local Search (PLS) is a basic building block in many multiobjective metaheuristics. In this paper, Parallel Pareto Local Search based on Decomposition (PPLS/D) is proposed. PPLS/D decomposes the original search space into L subregions and executes L parallel search processes in these subregions simultaneously. Inside each subregion, the PPLS/D process is first guided by a scalar objectiv...

Enumeration strategies (that is, selection of a variable and a value of its domain) are crucial components of Constraint Programming: they significantly influence the performances of the solving process, sometimes of several orders of magnitude. In this paper, we propose to use Local Search in order to help and guide enumeration: we extend the usual variable selection strategies of constraint p...

Neural Architecture Search (NAS), i.e., the automation of neural network design, has gained much popularity in recent years with increasingly complex search algorithms being proposed. Yet, solid comparisons simple baselines are often missing. At same time, retrospective studies have found many new to be no better than random (RS). In this work we consider use a Local (LS) algorithm for NAS. We ...

Randomized search methods have greatly extended our ability to solve hard computational problems. In general, however, we think of randomization in the context of local search. While local search methods have proved to be very powerful, in some situations they cannot supplant complete or exact methods due to their inherent limitation: Local search methods cannot prove inconsistency or

We propose a new local search platform that splits a CNF formula into three sub-components: i) a minimal dependency lattice (representing the core connections between logic gates), ii) a conjunction of equivalence clauses, and iii) the remaining clauses. We also adopt a new hierarchical cost function that focuses on solving the core components of the problem first. We then show experimentally t...

Clause weighting local search methods are widely used for satisfiability testing. A feature of particular importance for such methods is the scheme used to maintain the clause weight distribution relevant to different areas of the search landscape. Existing methods periodically adjust clause weights either multiplicatively or additively. Tie breaking strategies are used whenever a method’s eval...

This paper deals with the Vehicle Routing Problem with Simultaneous Pick-up and Delivery and Time Limit (VRPSPDTL). Due to the combinatorial nature of the problem, heuristics methods are commonly used to generate good quality solutions within an acceptable computational time. Accordingly, an Iterated Local Search (ILS) procedure that uses a Variable Neighborhood Descent (VND) method to perform ...

Systematic search and local search paradigms for combinatorial problems are generally believed to have complementary strengths. Nevertheless, attempts to combine the power of the two paradigms have had limited success, due in part to the expensive information communication overhead involved. We propose a hybrid strategy based on shared memory, ideally suited for multi-core processor architectur...