http://hdl.handle.net/10174/14454 2026-04-06T09:30:37Z 2026-04-06T09:30:37Z Mateusz, Ślażyński Salvador, Abreu Grzegorz, Nalepa http://hdl.handle.net/10174/25724 2019-07-22T16:45:34Z 2019-06-30T23:00:00Z

Title: Towards a formal specification of local search neighborhoods from a constraint satisfaction problem structure Authors: Mateusz, Ślażyński; Salvador, Abreu; Grzegorz, Nalepa Editors: López-Ibáñez, Manuel Abstract: Neighborhood operators play a crucial role in defining effective Local Search solvers, allowing one to limit the explored search space and prune the fitness landscape. Still, there is no accepted formal representation of such operators: they are usually modeled as algorithms in procedural language, lacking in compositionality and readability. In this paper we outline a new formalization capable of representing several neighborhood operators eschewing their coding in a full Turing complete language. The expressiveness of our proposal stems from a rich problem representation, as used in Constraint Programming models. We compare our system to competing approaches and show a clear increment in expressiveness.

2019-06-30T23:00:00Z Roque, Pedro Pedro, Vasco Diaz, Daniel Abreu, Salvador http://hdl.handle.net/10174/24781 2019-02-20T13:02:46Z 2018-11-01T00:00:00Z

Title: Improving Constraint Solving on Parallel Hybrid Systems Authors: Roque, Pedro; Pedro, Vasco; Diaz, Daniel; Abreu, Salvador Abstract: Recently, we developed the Parallel Heterogeneous Architecture Constraint Toolkit (PHACT), which is a multi-threaded constraint solver capable of using all the available devices which are compatible with OpenCL, in order to speed up the constraint satisfaction process. In this article, we introduce an evolution of PHACT which includes the ability to execute FlatZinc and MiniZinc models, as well as architectural improvements which boost the performance in solving CSPs, especially when using GPUs.

2018-11-01T00:00:00Z Lopez, Jheisson Munera, Danny Diaz, Daniel Abreu, Salvador http://hdl.handle.net/10174/24743 2019-02-18T16:13:09Z 2018-04-30T23:00:00Z

Title: On Integrating Population-Based Metaheuristics with Cooperative Parallelism Authors: Lopez, Jheisson; Munera, Danny; Diaz, Daniel; Abreu, Salvador Abstract: Many real-life applications can be formulated as Combinatorial Optimization Problems, the solution of which is often challenging due to their intrinsic difficulty. At present, the most effective methods to address the hardest problems entail the hybridization of metaheuristics and cooperative parallelism. Recently, a framework called CPLS has been proposed, which eases the cooperative parallelization of local search solvers. Being able to run different heuristics in parallel, CPLS has opened a new way to hybridize metaheuristics, thanks to its cooperative parallelism mechanism. However, CPLS is mainly designed for local search methods. In this paper we seek to overcome the current CPLS limitation, extending it to enable population-based metaheuristics in the hybridization process. We discuss an initial prototype implementation for Quadratic Assignment Problem combining a Genetic Algorithm with two local search procedures. Our experiments on hard instances of QAP show that this hybrid solver performs competitively w.r.t. dedicated QAP parallel solvers.

2018-04-30T23:00:00Z