L
Luiz Satoru Ochi
Researcher at Federal Fluminense University
Publications - 160
Citations - 3033
Luiz Satoru Ochi is an academic researcher from Federal Fluminense University. The author has contributed to research in topics: Metaheuristic & Iterated local search. The author has an hindex of 25, co-authored 149 publications receiving 2573 citations.
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Journal ArticleDOI
A parallel heuristic for the Vehicle Routing Problem with Simultaneous Pickup and Delivery
Anand Subramanian,Lúcia Maria de A. Drummond,Cristiana Bentes,Luiz Satoru Ochi,Ricardo Farias +4 more
TL;DR: The proposed algorithm not only improved several of the known solutions, but also presented a very satisfying scalability.
Journal ArticleDOI
A hybrid algorithm for a class of vehicle routing problems
TL;DR: A sequence of Set Partitioning (SP) models, with columns corresponding to routes found by a metaheuristic approach, are solved, not necessarily to optimality, using a Mixed Integer Programming (MIP) solver that may interact with theMetaheuristic during its execution.
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
A multi-objective green UAV routing problem
Bruno Nazário Coelho,Vitor Nazário Coelho,Igor Machado Coelho,Luiz Satoru Ochi,K Roozbeh Haghnazar,Demetrius Zuidema,Milton Sergio Fernandes de Lima,Adilson Rodrigues da Costa +7 more
TL;DR: A new real-time routing problem, in which different types of drones can collect and deliver packages, and seven different objective functions are considered and sought to be minimized using a Mixed-Integer Linear Programming (MILP) model solved by a matheuristic algorithm.