comparison of deterministic, fuzzy and possiblistic multi objective programming approaches: case of kohgilooye and boyerahmad province farmers

abstract regarding the imprecise or fuzzy data on the agriculture activities, applying models based on fuzzy data may be useful. in line with this condition this study tries to compare the ability of possiblistic programming approach in developing optimal solution with fuzzy and deterministic programming. to get this objective a data set obtained from 90 farmers of kohgilooye region, gathered in 1387(2008), was applied. goals regarded in the models are mainly to increase gross margin (gm), decrease risk and to decrease water consumption. in framework of possiblistic programming approach these goals are maximizing average gm, minimizing difference between average and minimum gm, maximizing difference between average and maximum gm. the goal of reducing water consumption also contains minimizing average water consumption, maximizing difference between average and minimum water consumption and minimizing difference between average and maximum water consumption. different optimal solutions was developed using the above models and then some of them were chosen based on the goals. findings showed that possiblistic programming has preference over the two other models in that is able to get the various and conflict goals and its superiority to other models is more noticeable as the number of goals increases. high ability in developing desired solution in bad condition is another superiority of possiblistic programming. it was also found that watermelon, rice and melon are more appropriate to get the goals. the results suggeat that in order to lessen the pressure on water resources, some efforts is needed to decrease the price and revenue fluctuations.