da Silva, Aneirson Francisco [UNESP]Silva Marins, Fernando Augusto [UNESP]Barra Montevechi, José Arnaldo2014-05-272014-05-272013-05-01Applied Mathematical Modelling, v. 37, n. 9, p. 6146-6162, 2013.0307-904Xhttp://hdl.handle.net/11449/75202Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.6146-6162engAggregate production planningGoal programmingMulti- Choice mixed integer goal programmingMulti-choice aspiration levelsSugar and ethanol millsAnalytical approachGoal programming modelMulti choicesMultiple aspiration levelsProduction processReal-world problemAggregatesEthanolIndustryInteger programmingLoadingMilling (machining)Production engineeringProblem solvingArtigo10.1016/j.apm.2012.12.022WOS:000317378900003Acesso restrito2-s2.0-84875377451