Optimizing Helicopter Transport of Oil Rig Crews at Petrobras

Fernanda Menezes (), Oscar Porto (), Marcelo L. Reis (), Lorenza Moreno (), Marcus Poggi de Aragão (), Eduardo Uchoa (), Hernán Abeledo () and Nelci Carvalho do Nascimento ()
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Fernanda Menezes: Gapso Tecnologia da Decisão, Rio de Janeiro-RJ, 22290-160, Brazil
Oscar Porto: Gapso Tecnologia da Decisão, Rio de Janeiro-RJ, 22290-160, Brazil
Marcelo L. Reis: Gapso Tecnologia da Decisão, Rio de Janeiro-RJ, 22290-160, Brazil
Lorenza Moreno: Departamento de Informática, Pontificia Universidade Católica, Rio de Janeiro-RJ, 22451-900, Brazil
Marcus Poggi de Aragão: Departamento de Informática, Pontificia Universidade Católica, Rio de Janeiro-RJ, 22451-900, Brazil
Eduardo Uchoa: Departamento de Engenharia de Produção, Universidade Federal Fluminense, Niteroi-RJ, 24210-240, Brazil
Hernán Abeledo: Department of Engineering Management and Systems Engineering, George Washington University, Washington, DC 20052
Nelci Carvalho do Nascimento: Serviços/Unidades de Serviços de Transporte e Armazenamento, Exploração e Produção, Petrobras, Macaé, Rio de Janeiro-RJ, 27915-012, Brazil

Interfaces, 2010, vol. 40, issue 5, 408-416

Abstract: Petrobras produces nearly 90 percent of Brazil's oil at about 80 offshore oil platforms. It transports approximately 1,900 employees daily between these platforms and four mainland bases, using more than 40 helicopters that vary in capacity, operating costs, and performance characteristics. Each day, flight planners must select the helicopter routes and schedules that satisfy passenger demands. We developed a system that requires less than one hour to generate optimized flight plans that meet operational guidelines, improve travel safety, and minimize operating costs. By using this system, Petrobras reduced its number of offshore landings by 18 percent, total flight time by 8 percent, and flight costs by 14 percent, resulting in annual savings of more than $20 million. Our optimization model is a large-scale mixed integer program that generalizes prior helicopter routing models. We designed a column-generation algorithm that exploits the problem structure to overcome its computational difficulties. As part of the solution method, we use a network flow model to optimally assign passengers to selected routes.

Keywords: helicopter scheduling; integer programming; column generation (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:40:y:2010:i:5:p:408-416

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