DECSI - Departamento de Computação e Sistemas de Informação
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Browsing DECSI - Departamento de Computação e Sistemas de Informação by Author "Araujo, Janniele Aparecida Soares"
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Item An integer programming approach to the multimode resource-constrained multiproject scheduling problem.(2015) Toffolo, Túlio Ângelo Machado; Santos, Haroldo Gambini; Carvalho, Marco Antonio Moreira de; Araujo, Janniele Aparecida SoaresThe project scheduling problem (PSP) is the subject of several studies in computer science, mathematics, and operations research because of the hardness of solving it and its practical importance. This work tackles an extended version of the problem known as the multimode resourceconstrained multiproject scheduling problem. A solution to this problem consists of a schedule of jobs from various projects, so that the job allocations do not exceed the stipulated limits of renewable and nonrenewable resources. To accomplish this, a set of execution modes for the jobs must be chosen, as the jobs’ duration and amount of needed resources vary depending on the mode selected. Finally, the schedule must also consider precedence constraints between jobs. This work proposes heuristic methods based on integer programming to solve the PSP considered in the Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA) 2013 Challenge. The developed solver was ranked third in the competition, being able to find feasible and competitive solutions for all instances and improving best known solutions for some problems.Item Strong bounds for resource constrained project scheduling : preprocessing and cutting planes.(2020) Araujo, Janniele Aparecida Soares; Santos, Haroldo Gambini; Gendron, Bernard; Jena, Sanjay Dominik; Brito, Samuel Souza; Souza, Danilo SantosResource Constrained Project Scheduling Problems (RCPSPs) without preemption are well-known N Phard combinatorial optimization problems. A feasible RCPSP solution consists of a time-ordered schedule of jobs with corresponding execution modes, respecting precedence and resources constraints. In this paper, 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-theart 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.