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Hibridizing heuristic and exact methods to approach combinatorial optimization problems

Abstract

The solution of combinatorial optimization problems remains a big challenge for researchers who aim at beyond quality of solutions low CPU time to achieve them. Exact methods are intractable and even the traditional heuristics can not be as efficient as expected for solving large scale instances, relevant to a number of applications. To determine high quality solutions, or even feasible, to the problem of sustainable supply chains, production planning and routing are also examples of barriers not yet overcome. Bearing these issues in mind, in this project, the researcher and collaborators (among them, master students, doctoral students, undergraduates and national and international researchers) will develop efficient methods, based on hybridization of exact methods and heuristics, primarily, to these combinatorial optimization problems. Besides that, we will study new models, stronger formulations. (AU)

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VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Scientific publications (16)
(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)
NAKAMURA, KATIA Y.; COELHO, LEANDRO C.; RENAUD, JACQUES; NASCIMENTO, MARIA C. V.. The Traveling Backpacker Problem: A computational comparison of two formulations. Journal of the Operational Research Society, v. 69, n. 1, p. 108-114, . (15/21660-4)
ROSSET, VALERIO; PAULO, MATHEUS A.; CESPEDES, JULIANA G.; NASCIMENTO, MARIA C. V.. Enhancing the reliability on data delivery and energy efficiency by combining swarm intelligence and community detection in large-scale WSNs. EXPERT SYSTEMS WITH APPLICATIONS, v. 78, p. 89-102, . (15/18580-9, 15/21660-4)
FRANCISQUINI, RODRIGO; NASCIMENTO, MARIA C. V.; BASGALUPP, MARCIO P.; IEEE. NGA-LP: A robust and improved genetic algorithm to detect communities in directed networks. 2018 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), v. N/A, p. 8-pg., . (16/02870-0, 15/21660-4)
JALAL, AURA M.; TOSO, ELI A. V.; TAUTENHAIN, CAMILA P. S.; NASCIMENTO, MARIA C. V.. An integrated location-transportation problem under value-added tax issues in pharmaceutical distribution planning. EXPERT SYSTEMS WITH APPLICATIONS, v. 206, p. 17-pg., . (13/07375-0, 17/07236-0, 14/27334-9, 15/21660-4)
CARVALHO, DESIREE M.; NASCIMENTO, MARIA C. V.. A kernel search to the multi-plant capacitated lot sizing problem with setup carry-over. Computers & Operations Research, v. 100, p. 43-53, . (16/02537-0, 13/07375-0, 15/21660-4)
CARVALHO, DESIREE M.; NASCIMENTO, MARIA C. V.. Lagrangian heuristics for the capacitated multi-plant lot sizing problem with multiple periods and items. Computers & Operations Research, v. 71, p. 137-148, . (15/21660-4)
MAXIMO, VINICIUS R.; NASCIMENTO, MARIA C. V.. Intensification, learning and diversification in a hybrid metaheuristic: an efficient unification. Journal of Heuristics, v. 25, n. 4-5, SI, p. 539-564, . (13/07375-0, 15/21660-4)
TAUTENHAIN, CAMILA P. S.; BARBOSA-POVOA, ANA PAULA; NASCIMENTO, V, MARIA C.. A multi-objective matheuristic for designing and planning sustainable supply chains. COMPUTERS & INDUSTRIAL ENGINEERING, v. 135, p. 1203-1223, . (13/07375-0, 14/27334-9, 16/02203-4, 15/21660-4)
CARVALHO, DESIREE M.; NASCIMENTO, V, MARIA C.. Hybrid matheuristics to solve the integrated lot sizing and scheduling problem on parallel machines with sequence-dependent and non-triangular setup. European Journal of Operational Research, v. 296, n. 1, p. 158-173, . (15/21660-4, 13/07375-0, 16/02537-0)
FRANCISQUINI, RODRIGO; BERTON, RAFAEL; SOARES, SANDRO GOMES; PESSOTTI, DAYELLE S.; CAMACHO, MAURICIO F.; ANDRADE-SILVA, DEBORA; BARCICK, UILLA; SERRANO, SOLANGE M. T.; CHAMMAS, ROGER; NASCIMENTO, MARIA C. V.; et al. Community-based network analyses reveal emerging connectivity patterns of protein-protein interactions in murine melanoma secretome. JOURNAL OF PROTEOMICS, v. 232, . (17/22330-3, 15/21660-4, 13/07375-0, 17/24185-0, 14/06579-3, 19/10817-0, 13/07467-1)
TAUTENHAIN, CAMILA P. S.; NASCIMENTO, MARIA C. V.; ROCHA, AP; STEELS, L; VANDENHERIK, J. Spectral Algorithm for Line Graphs to Find Overlapping Communities in Social Networks. PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE (ICAART), VOL 2, v. N/A, p. 12-pg., . (15/21660-4, 16/22688-2)
JESKE, MARLON; ROSSET, VALERIO; NASCIMENTO, MARIA C., V. Determining the trade-offs between data delivery and energy consumption in large-scale WSNs by multi-objective evolutionary optimization. Computer Networks, v. 179, p. 18-pg., . (15/21660-4, 15/18580-9)
MAXIMO, VINICIUS R.; NASCIMENTO, MARIA C. V.. Intensification, learning and diversification in a hybrid metaheuristic: an efficient unification. Journal of Heuristics, v. 25, n. 4-5, p. 26-pg., . (13/07375-0, 15/21660-4)
FRANCISQUINI, RODRIGO; ROSSET, VALERIO; NASCIMENTO, MARIA C. V.. GA-LP: A genetic algorithm based on Label Propagation to detect communities in directed networks. EXPERT SYSTEMS WITH APPLICATIONS, v. 74, p. 127-138, . (15/18580-9, 15/21660-4)
MAXIMO, VINICIUS R.; NASCIMENTO, MARIA C. V.; CARVALHO, ANDRE C. P. L. F.. Intelligent-guided adaptive search for the maximum covering location problem. Computers & Operations Research, v. 78, p. 129-137, . (13/07375-0, 10/20231-9, 15/21660-4)
TAUTENHAIN, CAMILA P. S.; NASCIMENTO, V, MARIA C.. An ensemble based on a bi-objective evolutionary spectral algorithm for graph clustering. EXPERT SYSTEMS WITH APPLICATIONS, v. 141, . (16/22688-2, 15/21660-4)

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