Mathematical models and solution methods for large-scale combinatorial optimization problems

• Grant number: 22/03182-1
• Support Opportunities: Research Grants - Initial Project
• Start date: February 01, 2023
• End date: January 31, 2028
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Leonardo Junqueira
• Grantee: Leonardo Junqueira
• Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• City of the host institution: São Paulo
• Associated scholarship(s): 24/11515-6 - Optimized generation of sports competition tables: equity considerations between teams in the Brazilian Football Championship, BP.IC

Abstract

This research project addresses combinatorial optimization problems belonging to five problem classes. In general, the problems addressed involve the optimization (minimization or maximization) of specific objectives and a discrete set of feasible solutions, while they may be subject to a number of practical considerations. In particular, due to the advancing complexities of society, the conception of mathematical models and solution methods has resorted to an increasing number of variables and constraints, in order to keep the solutions obtained realistic and adherent to practical contexts. Concisely, the objectives of this project include: (i) the study, review and classification of the literature of each of the problems addressed; (ii) the development of mathematical programming models based on mixed integer linear programming to describe some of the problems addressed; (iii) the development of solution methods based on exact, heuristic/metaheuristic, or hybrid approaches to solve some of the problems addressed; (iv) the analysis and comparison of the performance of the proposed models and methods while solving instances from real situations where the problems addressed occur, obtained from the literature, or randomly generated. (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)

RODRIGUES, GUSTAVO DE ABREU; JUNQUEIRA, LEONARDO; VIEIRA, JOSE GERALDO VIDAL; DA SILVA JUNIOR, ORIVALDE SOARES; DA CUNHA, CLAUDIO BARBIERI. Rural last-mile distribution using a hybrid heuristic-multi-criteria decision-making framework. EXPERT SYSTEMS WITH APPLICATIONS, v. 289, p. 19-pg., 2025-09-15. (22/05803-3, 22/03182-1)

SANTORO, MIGUEL CEZAR; JUNQUEIRA, LEONARDO. Unrelated parallel machine scheduling models with machine availability and eligibility constraints. COMPUTERS & INDUSTRIAL ENGINEERING, v. 179, p. 16-pg., 2023-04-14. (22/03182-1, 16/01860-1)