IN THIS PAPER A NEW METHOD IS SUGGESTED FOR SOLVING MULTI-OBJECTIVE LINEAR FRACTIONAL PROGRAMMING PROBLEM. THE PROPOSED METHOD IS BASED UPON TRANSFORMING TO MULTI-OBJECTIVE LINEAR PROGRAMMING PROBLEM BY USING V.JOSHI, E.SINGH, N.GUPTA, PRIMAL-DUAL APPROACH TO SOLVE LINEAR FRACTIONAL PROGRAMMING PROBLEM, JOURNAL OF THE APPLIED MATHEMATICS, STATISTICS AND INFORMATICS (JAMSI), 4 (2008), NO.1. IN THE END, THE PROPOSED METHOD HAVE BEEN UTILIZED FOR EXAMPLES.

MULTI OBJECTIVE LINEAR PROGRAMMING OR GOAL PROGRAMMING TECHNIQUE WAS USED IN ORDER TO DETERMINE THE OPTIMAL FOREST PLANTATION IN NORTH OF IRAN. THE OBJECTIVE WAS MAXIMIZING NET PRESENT VALUE, NUMBER OF LABOR AND CARBON SEQUESTRATION. REQUIRED DATA INCLUDING GROWTH, STUMPAGE PRICE, CARBON SEQUESTRATION AND NUMBER OF LABOR WAS COLLECTED. REGRESSION ANALYSIS WAS USED TO DERIVE GROWTH MODELS. EXPECTED MEAN PRICE WAS ESTIMATED USING WOOD PRICE AND VARIABLE HARVESTING COSTS. LINGO SOFTWARE WAS USED FOR ANALYSIS. RESULTS INDICATED THAT THE OPTIMAL PLANTATION FOR OAK, ASH AND LOBLOLLY PINE ARE 149.37, 136.72 AND 206.20 HA, RESPECTIVELY.

WE CONSIDER BILEVEL LINEAR MULTI-OBJECTIVE PROGRAMMING PROBLEMS (BLMPP) IN WHICH THEDECISION MAKER HAS MULTIPLE OBJECTIVE FUNCTIONS CONFLICTING WITH EACH OTHER AT EACH LEVEL. WE SHOW HOW TO CONSTRUCT TWO ARTIFICIAL MULTI-OBJECTIVE PROGRAMMING PROBLEMS SUCH THAT ANY POINTTHAT IS EFFICIENT FOR BOTH PROBLEMS IS AN EFFICIENT SOLUTION OF THE BLMPP. A NECESSARY AND SUFFICIENTCONDITION WHICH IS APPLICABLE FOR THE OBTAINED RESULT IS PROVIDED. THEN, BASED ON THESE RESULTS, THE ALGORITHM IS PRESENTED. FINALLY, WE GIVE AN EXAMPLE TO SHOW THE EFFICIENCY OF THE ALGORITHM.