A heuristic for large-sizep-median location problems with application to school location

Pizzolato, Nélio Domingues

doi:10.1007/bf02085654

Cited by 33 publications

(15 citation statements)

References 12 publications

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“…O desenvolvimento de modelos matemáticos de localização e distribuição representa uma importante ferramenta de aplicação da Pesquisa Operacional (PO). Autores [6], [15], [16], [17], [18], [19] apresentam modelos consolidados de localização de escolas. Como visto em diversos estudos, estes modelos em geral definem parâmetros para o modelo, como capacidade total da unidade escolar, custo, distância etc, porém não discutem os cálculos dos parâmetros do modelo bem como o detalhas operacionais relacionados à situação real de infraestrutura da unidade de escolar.…”

Section: Parametros Do Modelo De Localização De Escolas No Municipio unclassified

Cálculo De Parâmetros Para O Problema De Localização De Escolas No Municipio De Macaé

Moura¹,

Ignacio²

2016

Anais Do XVIII Simpósio De Pesquisa Operacional &Amp; Logística Da Marinha

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ResumoApesar de o Brasil ter obtido progressos expressivos no campo da educação nas últimas décadas, o país ainda enfrenta a dificuldade de atendimento à grande parcela da população. Muito se deve ao processo de urbanização desordenado, com isso existe a dificuldade do atendimento as áreas localizadas fora da mancha urbana, o que impacta diretamente a rede escolar. Em Macaé o impacto é grave, uma vez que este município conhecido como a capital do petróleo, também é o município brasileiro que mais cresce e encontra-se despreparado para os impactos resultantes de intensos processos migratórios. Investir fortemente na educação infantil, conferindo centralidade no atendimento das crianças de 0 a 5 anos, é a tarefa e o grande desafio do município. Para isso, é essencial o levantamento detalhado da demanda por creche e pré-escola, de modo a materializar o planejamento da expansão e a melhoria das unidades já existentes. No presente artigo é feita uma delimitação das questões referentes à infraestrutura da área de educação, de modo que ao final se tenha uma boa quantidade de dados que possam ser tratados matematicamente e contribuam para a elaboração de uma proposta metodológica consistente. Palavras-Chaves:Programação Matemática; Medianas; Modelagem; Educação; Macaé; Abstract Although Brazil has achieved significant progress in education in recent decades, the country still faces the difficulty of compliance with most of the population. Much is due to the disorderly urbanization process, therefore there is the difficulty of the service areas located outside the urban area, which directly impacts the school network. In Macaé the impact is severe, since this city known as the oil capital, is also the Brazilian city's fastest growing and is unprepared for the impacts of intensive migration processes. Invest heavily in early childhood education, giving centrality in the care of children 0-5 years, it is the task and the challenge of the municipality. Therefore, it is essential the detailed survey of the demand for day care and pre-school, in order to materialize the planning of expansion and improvement of existing units. In this paper a definition of matters relating to the infrastructure of the area of education, so that in the end it has a good amount of data that can be treated mathematically and contribute to the development of a consistent methodological approach.

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Section: Parametros Do Modelo De Localização De Escolas No Municipio unclassified

Cálculo De Parâmetros Para O Problema De Localização De Escolas No Municipio De Macaé

Moura¹,

Ignacio²

2016

Anais Do XVIII Simpósio De Pesquisa Operacional &Amp; Logística Da Marinha

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“…Regarding educational facilities, many proposals exist in literature with respect to investment in capacity: aperture, closure or expansion. Among these types of works we have: Greenleaf and Harrison (1987), Henig and Gerschak (1986), Pizzolato (1994), Tewari and Jena (1987), and Viegas (1987), but none of them seek to approach the term of capacity from their results but rather from the resources delivered as a multiple or a proportion of what is already built.…”

Section: Capacity In Educational Institutionsmentioning

confidence: 99%

Simulation-optimization model to determine the installed capacity of an educational services system

González

Velásquez

Cabrera

2016

Rev. Lasallista Investig.

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Introduction. The problem of determining the capacity in service companies is the lack of clear methodologies. As for academic institutions, the research advances on the subject are even more reduced. The literature available has widely covered other problems affecting capacity, and also the programming and the planning of staff, facilities and schedules without directly measuring capacity. Objective. To create a generic methodology to determine the capacity of an educative services system (schools, universities, etc) in terms of the quantity of students to serve with the institution´s infrastructure. Materials and methods. Firstly, a methodology to simulate the capacity used by the students throughout time is created. Then, with this information, an optimization model to calculate the maximum number of students that can be admitted is executed. Results. The model developed is applied in the Engineering School of Universidad del Valle, Colombia, where it was found that 25% more of students could have been admitted, using about 20 % of the capacity that can be potentially used. Conclusion. This methodological model is useful to know the capacity in terms of the number of students an institution can receive. It also facilitates midterm decisions, especially the measurement of the impact of the policies that can be formulated to favor the maximization of the service standards of the institution, and also, for instance, the impact of building new infrastructures.

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“…For example, in the GreedyG heuristic (Captivo, 1991), in each step of Greedy, the Alternate procedure is run. A combination of Alternate and Interchange heuristics has been suggested in Pizzolato (1994). In Moreno- Pérez et al (1991), a variant of Stingy (or GreedyDrop) is compared with Greedy + Alternate and Multistart Alternate.…”

Section: Test Problemsmentioning

confidence: 99%

The p-median problem: A survey of metaheuristic approaches

Mladenović

Brimberg

Hansen

et al. 2007

European Journal of Operational Research

367

182

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Abstract. The p-median problem, like most location problems, is classified as N P -hard, and so, heuristic methods are usually used for solving it. The pmedian problem is a basic discrete location problem with real application that have been widely used to test heuristics. Metaheuristics are frameworks for building heuristics. In this survey, we examine the p-median, with the aim of providing an overview on advances in solving it using recent procedures based on metaheuristic rules.

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A heuristic for large-sizep-median location problems with application to school location

Cited by 33 publications

References 12 publications

Cálculo De Parâmetros Para O Problema De Localização De Escolas No Municipio De Macaé

Cálculo De Parâmetros Para O Problema De Localização De Escolas No Municipio De Macaé

Simulation-optimization model to determine the installed capacity of an educational services system

The p-median problem: A survey of metaheuristic approaches

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