Autor(es): Lopez, Jheisson ; Munera, Danny ; Diaz, Daniel ; Abreu, Salvador
Data: 2019
Identificador Persistente: http://hdl.handle.net/10174/24749
Origem: Repositório Científico da Universidade de Évora
Autor(es): Lopez, Jheisson ; Munera, Danny ; Diaz, Daniel ; Abreu, Salvador
Data: 2019
Identificador Persistente: http://hdl.handle.net/10174/24749
Origem: Repositório Científico da Universidade de Évora
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.