http://hdl.handle.net/10174/14465 2026-04-05T14:51:01Z http://hdl.handle.net/10174/24749 Title: Weaving of Metaheuristics with Cooperative Parallelism Authors: Lopez, Jheisson; Munera, Danny; Diaz, Daniel; Abreu, Salvador Abstract: We propose PHYSH (Parallel HYbridization for Simple Heuristics), a framework to ease the design and implementation of hybrid metaheuristics via cooperative parallelism. With this framework, the user only needs encode each of the desired metaheuristics and may rely on PHYSH for parallelization, cooperation and hybridization. PHYSH supports the combination of population-based and single-solution metaheuristics and enables the user to control the tradeoff between intensification and diversification. We also provide an open-source implementation of this framework which we use to model the Quadratic Assignment Problem (QAP) with a hybrid solver, combining three metaheuristics. We present experimental evidence that PHYSH brings significant improvements over competing approaches, as witness the performance on representative hard instances of QAP. 2018-08-31T23:00:00Z http://hdl.handle.net/10174/23639 Title: Improving Constraint Solving on Parallel Hybrid Systems Authors: Roque, Pedro; Pedro, Vasco; Diaz, Daniel; Abreu, Salvador Editors: Alamaniotis, Miltos 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 http://hdl.handle.net/10174/23637 Title: Weaving of Metaheuristics with Cooperative Parallelism Authors: Lopez, Jheisson; Munera, Danny; Diaz, Daniel; Abreu, Salvador Editors: Auger, Anne; Fonseca, Carlos; Lourenço, Nuno; Machado, Penousal; Paquete, Luís; Whitley, Darrell Abstract: We propose PHYSH (Parallel HYbridization for Simple Heu-ristics), a framework to ease the design and implementation of hybridmetaheuristics via cooperative parallelism. With this framework, theuser only needs encode each of the desired metaheuristics and may relyon PHYSH for parallelization, cooperation and hybridization. PHYSHsupports the combination of population-based and single-solution meta-heuristics and enables the user to control the tradeoff between intensifi-cation and diversification. We also provide an open-source implementa-tion of this framework which we use to model the Quadratic AssignmentProblem (QAP) with a hybrid solver, combining three metaheuristics.We present experimental evidence that PHYSH brings significant im-provements over competing approaches, as witness the performance onrepresentative hard instances of QAP 2018-01-01T00:00:00Z