Comunidades no Repositório Institucional
Selecione uma comunidade para navegar por suas coleções
Agora exibindo 1 - 11 de 11
Escola de Filosofia, Letras e Ciências Humanas (EFLCH) Escola Paulista de Enfermagem (EPE) Escola Paulista de Medicina (EPM) Escola Paulista de Política, Economia e Negócios (EPPEN) Instituto das Cidades (IC) Instituto de Ciência e Tecnologia (ICT) Instituto de Ciências Ambientais, Químicas e Farmacêuticas (ICAQF) Instituto de Saúde e Sociedade (ISS) Instituto do Mar (IMar) Reitoria UNIFESP
Submissões Recentes
Item
Entenda as diferenças entre as Unidades de saúde
(Universidade Federal de São Paulo (UNIFESP), 2022) Rodrigues, Giovana [UNIFESP]; Ribeiro, Juliana Maria Martins [UNIFESP]; Contardi, Luane [UNIFESP]; Bandeira, Brenda [UNIFESP]; Bartolomeu, Victoria Castilho [UNIFESP]; Rios, Andressa [UNIFESP]; Silva, Milena Perez de Lima Marques [UNIFESP]; http://lattes.cnpq.br/9352899576424852
Elaboração de um post destinado à população em geral, abordando as diferenças das unidades de saúde e sua importância.
Item
Folder grupo de gestantes
(Universidade Federal de São Paulo, 2024) Bandeira, Brenda [UNIFESP]; Cirqueira, Raiane [UNIFESP]; Silva, Milena Perez de Lima Marques [UNIFESP]; Matos, Natália Furtado de [UNIFESP]; Oliveira, Mateus Santos de Lima [UNIFESP]; Westphal, Flávia [UNIFESP]; http://lattes.cnpq.br/9352899576424852; http://lattes.cnpq.br/7832457453349192
Folder elaborado na disciplina de Saúde da Mulher 1 destinado ao grupo de gestantes da UBS Vila Clara, contendo informações relacionadas ao 1 trimestre como: vacinas necessárias, suplementação, calendário de consultas e sinais/ sintomas relacionados ao período gestacional.
Item
A parallel branch-and-cut and an adaptive metaheuristic to solve the family traveling salesman problem
(Elsevier, 2023) Chaves, Antonio Augusto [UNIFESP]; Vianna, Barbara Lessa [UNIFESP]; Silva, Tiago Tibúrcio da [UNIFESP]; Schenekemberg, Cleder Marcos [UNIFESP]; http://lattes.cnpq.br/4973949421738244
This paper addresses the Family Traveling Salesman Problem (FTSP), a variant of the Traveling Salesman Problem that group nodes into families. The goal is to select the best route by visiting only a subset of nodes from each family. We developed two methods to solve the FTSP: (i) a parallel branch- and-cut algorithm with an efficient local search procedure (P-B&C) to obtain an optimal solution, and (ii) an adaptive metaheuristic that combines the Biased Random-key Genetic Algorithm (BRKGA) with a reinforcement learning algorithm. In this case, the Q-Learning algorithm controls the parameters of the BRKGA during the evolutionary process. We perform computational experiments on a well-known benchmark dataset with 185 instances. Our P-B&C proves the optimal value for 179 instances, improving the best upper bounds in 19 open instances. The new local search component of the P-B&C finds the best upper bounds for 50% of instances. The BRKGA-QL finds the optimal solution in 131 instances, improving the best upper bounds in 21 open instances. Finally, we compare our results with the best results in the literature, and both methods show robustness and efficiency in solving the FTSP.
Item
Hybrid metaheuristics to solve a multi-product two-stage capacitated facility location problem
(Wiley, 2021) Chaves, Antonio Augusto [UNIFESP]; Mauri, Geraldo Regis; Biajoli, Fabricio Lacerda [UNIFESP]; Rabello, Rômulo Louzada; Ribeiro, Glaydston Mattos; Lorena, Luiz Antônio Nogueira [UNIFESP]; http://lattes.cnpq.br/4973949421738244
This paper presents two hybrid metaheuristics to solve a multi-product two-stage capacitated facility location prob- lem (MP-TSCFLP). In this problem, a set of different products must be transported from a set of plants to a set of intermediate depots (first stage) and from these depots to a set of customers (second stage). The objective is to minimize the cost related to open plants and depots plus the cost for transporting the products from the plants until the customers satisfying demand and capacity constraints. Recently, the methods Clustering Search (CS) and Biased Random-Key Genetic Algorithm (BRKGA) were successfully applied to solve a single-product problem (SP-TSCFLP). Therefore, in this paper we propose adaptations and implementations of these methods for handling with a multi-product approach. To the best of our knowledge, CS and BRKGA presented the best results for the SP-TSCFLP and both have not yet been applied to solve the problem with multiple products. Four sets of large- sized instances with different characteristics are proposed and computational experiments compare the obtained results to those from a commercial solver.
Item
A new multicommodity flow model for the job sequencing and tool switching problem
(Taylor and Francis Online, 2021) Chaves, Antonio Augusto [UNIFESP]; Silva, Tiago Tiburcio da [UNIFESP]; Yanasse, Horacio Hideki [UNIFESP]; http://lattes.cnpq.br/4973949421738244
In this paper a new multicommodity flow mathematical model for the Job Sequencing and Tool Switching Problem (SSP) is presented. The proposed model has a LP relaxation lower bound equal to the number of tools minus the tool machine’s capacity. Computational tests were performed comparing the new model with the models of the literature. The proposed model performed better, both in execution time and in the number of instances solved to optimality.