Defesa de Tese de Doutorado - Janniele Aparecida Soares Araujo

Dezembro 4, 2019

Data: 06/12/2019 - Horário: 13:30
Local: Sala de Seminários DECOM-UFOP
Aluna: Janniele Aparecida Soares Araujo
Orientador: Haroldo Gambini Santos
Título: Mixed-Integer Linear Programming Based Approaches for the Resource Constrained Project Scheduling Problem
Prof. Dr. Haroldo Gambini Santos (UFOP)
Prof. Dr. Eduardo Uchoa Barboza (UFF)
Prof. Dr. Marcone Jamilson Freitas Souza (UFOP)
Prof. Dr. Túlio Ângelo Machado Toffolo(UFOP)
Prof. Dr. Sanjay Dominik Jena(ESG UQAM)

Resource Constrained Project Scheduling Problems (RCPSPs) without preemption are well-known NP-hard combinatorial optimization problems. A feasible RCPSP solution consists of a time-ordered schedule of jobs with corresponding execution modes, respecting precedence and resource constraints. First, in this thesis, we provide improved upper bounds for many hard instances from the literature by using methods based on Stochastic Local Search (SLS). As the most significant part of this work, we propose a cutting plane algorithm to separate five different cut families, as well as a new preprocessing routine to strengthen resource-related constraints. New lifted versions of the well-known precedence and cover inequalities are employed. At each iteration, a dense conflict graph is built considering feasibility and optimality conditions to separate cliques, odd-holes and strengthened Chvátal-Gomory cuts. The proposed strategies considerably improve the linear relaxation bounds, allowing a state-of-the-art mixed-integer linear programming solver to find provably optimal solutions for 754 previously open instances of different variants of the RCPSPs, which was not possible using the original linear programming formulations.