Artículos de revistas
Hybridizing a multi-objective simulated annealing algorithm with a multi-objective evolutionary algorithm to solve a multi-objective project scheduling problem
Amandi, Analia Adriana; Yannibelli, Virginia Daniela; Hybridizing a multi-objective simulated annealing algorithm with a multi-objective evolutionary algorithm to solve a multi-objective project scheduling problem; Elsevier; Expert Systems with Applications; 40; 7; 11-2012; 2421-2434
Yannibelli, Virginia Daniela
Amandi, Analia Adriana
In this paper, a multi-objective project scheduling problem is addressed. This problem considers two conflicting, priority optimization objectives for project managers. One of these objectives is to minimize the project makespan. The other objective is to assign the most effective set of human resources to each project activity. To solve the problem, a multi-objective hybrid search and optimization algorithm is proposed. This algorithm is composed by a multi-objective simulated annealing algorithm and a multi-objective evolutionary algorithm. The multi-objective simulated annealing algorithm is integrated into the multi-objective evolutionary algorithm to improve the performance of the evolutionary-based search. To achieve this, the behavior of the multi-objective simulated annealing algorithm is self-adaptive to either an exploitation process or an exploration process depending on the state of the evolutionary-based search. The multi-objective hybrid algorithm generates a number of near non-dominated solutions so as to provide solutions with different trade-offs between the optimization objectives to project managers. The performance of the multi-objective hybrid algorithm is evaluated on nine different instance sets, and is compared with that of the only multi-objective algorithm previously proposed in the literature for solving the addressed problem. The performance comparison shows that the multi-objective hybrid algorithm significantly outperforms the previous multi-objective algorithm.
Showing items related by title, author, creator and subject.
Pavelski, Lucas Marcondes (Universidade Tecnológica Federal do ParanáCuritibaBrasilPrograma de Pós-Graduação em Engenharia Elétrica e Informática IndustrialUTFPR, 2021-12-13)The search for the best algorithm and its configuration is a difficult task on most optimization scenarios, especially on NP-hard problems, since different proposed metaheuristics exist, and testing many parameters demands ...
Martins, Marcella Scoczynski Ribeiro (Universidade Tecnológica Federal do ParanáCuritibaBrasilPrograma de Pós-Graduação em Engenharia Elétrica e Informática IndustrialUTFPR, 2017-12-11)Nowadays, a number of metaheuristics have been developed for dealing with multiobjective optimization problems. Estimation of distribution algorithms (EDAs) are a special class of metaheuristics that explore the decision ...
Florez, Martha Johanna Sepulveda; Chau, Wang Jiang; Gogniat, Guy; Strum, Marius (SPRINGERDORDRECHT, 2012)Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario ...