P
Puca Huachi Vaz Penna
Researcher at Universidade Federal de Ouro Preto
Publications - 29
Citations - 842
Puca Huachi Vaz Penna is an academic researcher from Universidade Federal de Ouro Preto. The author has contributed to research in topics: Vehicle routing problem & Metaheuristic. The author has an hindex of 10, co-authored 27 publications receiving 664 citations. Previous affiliations of Puca Huachi Vaz Penna include Federal Fluminense University.
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An Iterated Local Search heuristic for the Heterogeneous Fleet Vehicle Routing Problem
TL;DR: The proposed algorithm is based on the Iterated Local Search (ILS) metaheuristic which uses a Variable Neighborhood Descent procedure, with a random neighborhood ordering (RVND), in the local search phase, which is the first ILS approach for the HFVRP.
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A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem
TL;DR: The proposed hybrid algorithm is composed by an Iterated Local Search (ILS) based heuristic and a Set Partitioning (SP) formulation, which is solved by means of a Mixed Integer Programming solver that interactively calls the ILS heuristic during its execution.
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A Variable Neighborhood Search for Flying Sidekick Traveling Salesman Problem
TL;DR: This work proposes a hybrid heuristic that the initial solution is created from the optimal TSP solution reached by a TSP solver, and provides a new set of instances based on well-known TSPLIB instances.
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Large Neighborhoods with Implicit Customer Selection for Vehicle Routing Problems with Profits
TL;DR: A new neighborhood search is proposed for vehicle routing problems with profits, which explores an exponential number of solutions in pseudo-polynomial time and achieves an average gap on classic team orienteering benchmark instances, rivaling with the current state-of-the-art metaheuristics.
Journal ArticleDOI
An iterated local search heuristic for multi-capacity bin packing and machine reassignment problems
Renaud Masson,Renaud Masson,Thibaut Vidal,Thibaut Vidal,Julien Michallet,Puca Huachi Vaz Penna,Vinicius Petrucci,Anand Subramanian,Hugues Dubedout +8 more
TL;DR: An efficient Multi-Start Iterated Local Search for Packing problems (MS-ILS-PPs) metaheuristic for Multi-Capacity Bin Packing Problems (MCBPP) and Machine Reassignment Problems (MRP) is proposed, yielding the best known solutions and optimum ones in most cases.