Goal programming and data envelopment analysis (GPDEA) model to evaluate hiring process for offshore vessels for an oil company

Abstract

This article aims to develop and implement a Goal Programming and Data Envelopment Analysis (GPDEA) model to evaluate the efficiency of the hiring process for offshore vessels for an oil company. This situation features a number of technical, economic and legal requirements that are necessary for offshore logistics operations, and it has been treated by other authors by means a traditional DEA model. In a real problem addressed, the twenty vessels candidates for hiring by the company were considered to be the decision making units (DMUs ) and , for each , were analyzed seven (7) variables , two ( 2 ) variables input  and five ( 5 ) output variables. The inputs evaluated for each vessel were: the value of the daily cost of chartering and fuel consumption. The outputs evaluated for each vessel were: total storage capacity of potable water, the total storage capacity of diesel, the total storage capacity of deck cargo, the maximum continuous power of propulsion, and the maximum speed to be reached during navigation. The two models, DEA and GPDEA, were applied to the same database and we compared their performance on the choice of DMU (vessel) more interesting to be hired by the company. It was observed that the application of GPDEA allowed a better discrimination of the alternatives analyzed, facilitating decision making in hiring offshore vessels for an oil company. The concepts of inverted frontier, composite and normalized frontier, and super efficiency were tested to improve the discrimination of DMUs for both models.