New hybrid methods to resolve combinatorial optimization problems

• Grant number: 12/17523-3
• Support Opportunities: Research Grants - Young Investigators Grants
• Duration: January 01, 2013 - December 31, 2015
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Antônio Augusto Chaves
• Grantee: Antônio Augusto Chaves
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil
• Associated researchers: Álvaro Luiz Fazenda ; Edson Luiz França Senne ; Kelly Cristina Poldi ; Luiz Antonio Nogueira Lorena
• Associated grant(s): 18/15417-8 - Development of a hybrid metaheuristic with adaptive control flow and parameters, AP.JP2
• Associated scholarship(s): 15/06876-0 - Clustering Search applied to the capacitated centered clustering problem: a parallel approach, BP.IC; 14/00580-0 - New hybrid method with detection of promising areas for combinatorial optimization problems, BP.MS

Abstract

Over the last decades, studies concerning efficient metaheuristics has risen considerably among researchers in combinatorial optimization. Hybrid metaheuristics, in particular, has found the best results for many optimization problems. The main goal of this project is to develop and improve new alternatives for the hybrid Clustering Search method (CS), making it flexible, robust and efficient both in terms of the quality of the solutions and the computational effort. We intend to research this project through three different sub-research lines which include: the development of a new way of detecting promising areas, the designing of a multiobjective CS and the exploration of ways to parallelize the CS. These proposed methods are applied to resolve different optimization problems with many practical applications. The computational tests will use cases available in the literature and if possible, real cases using data from companies in the region. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CHAVES, A. A.; LORENA, L. A. N.; SENNE, E. L. F.; RESENDE, M. G. C.. Hybrid method with CS and BRKGA applied to the minimization of tool switches problem. Computers & Operations Research, v. 67, p. 174-183, MAR 2016. (12/17523-3)

ARAUJO, ELISEU JUNIO; CHAVES, ANTONIO AUGUSTO; DE SALLES NETO, LUIZ LEDUINO; DE AZEVEDO, ANIBAL TAVARES. Pareto clustering search applied for 3D container ship loading plan problem. EXPERT SYSTEMS WITH APPLICATIONS, v. 44, p. 50-57, FEB 2016. (12/17523-3)

MORALES, DAVI MELO; CHAVES, ANTONIO AUGUSTO; FAZENDA, ALVARO LUIZ; IEEE. Parallel Clustering Search applied to Capacitated Centered Clustering Problem. 2018 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW 2018), v. N/A, p. 7-pg., 2019-01-01. (15/24485-9, 12/17523-3, 14/50937-1)