A mathematical model and a Clustering Search metaheuristic for planning the helicopter transportation of employees to the production platforms of oil and gas. (November 2016)

• Record Type: Journal Article
• Authors: Rosa, Rodrigo de Alvarenga; Machado, André Manhães; Ribeiro, Glaydston Mattos; Mauri, Geraldo Regis
• Is Part Of: Computers & industrial engineering. Volume 101(2016)
• Page Start: 303
• Page End: 312
• Publication Date: 2016-11
• Subjects: Capacitated Helicopter Routing Problem -- Clustering Search -- Oil and gas logistics; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2016.09.006
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A mathematical model with new constraints for the Capacitated Helicopter Routing Problem. A Clustering Search (CS) metaheuristic for the Capacitated Helicopter Routing Problem. The model considers the transport between airport to platforms and between platforms. CS was able to solve instances with up to 1000 requests and 100 helicopters. This paper is motivated by a real logistic problem of a Brazilian Oil & Gas company. Abstract: In several countries, the petroleum is explored offshore and the oil and gas companies use oil drilling facilities and platforms far away from the coast. Thus, the oil companies transport its employees by helicopters between onshore basins, airports and platforms. This problem is known as the Capacitated Helicopter Routing Problem (CHRP). In this paper, it is proposed a formal mathematical model to the CHRP with several specific constraints and a more realistic objective function. Besides a Clustering Search (CS) metaheuristic is proposed to solve it. The mathematical model and the CS metaheuristic were tested with real data from a Brazilian oil and gas company. A set of instances with up to 1000 transportation requests and 100 helicopters was generated. Computational experiments indicate that CPLEX is not able to solve optimally even small instances of the problem, but the CS metaheuristic is capable of solving the proposed model generating good, stable and fast solutions.