03527nam a2200397 4500 20260818143701.0 160398 th eng .b10367718 AIT Thesis no. 1117 Guevara, Lauro D. Interactive approaches for solving multi-criterion optimization problems Bangkok : Asian Institute of Technology, 1977 100 p. Thesis ; no. 1117 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering of the Asian Institute of Technology, Bangkok, Thailand Thesis (M.Eng.) - Asian Institute of Technology, 1977 This thesis proposes two interactive approaches for solving multicriterion linear optimization problems: (1) "Trade-off Tracking" Approach via Sensitivity Analysis, and (2) "Multiobjective Equal Suboptimization Technique" or the MEST. "Equal Suboptimization" is given particular attention and is further used for solving problems involving quadratic goals. MEST is partly applied whenever there are two or more linear goals. The "Trade-off Tracking" belongs to the indifference mapping family where relationships of various goals are traced and identified prior to actual setting of targets or levels of performance. It is viewed as an extension of the idea contained in the technique called the Sequential Conversion of Goals into Constraints which is partly refuted in this paper. In the proposed technique, a reference function is to be selected and the other goals will be quantified in terms of the previously chosen criterion or reference goal. Relationships will be formulated for all possible ranges using the sensitivity analysis termed "Consequence Realization". Along the lines of the STEP Method (STEM) and the Game Theory Approach, the "Multiobjective Equal Suboptimization Technique" or the MEST has been visualized. In here, "equal suboptimization" will be measured with respect to permissible levels or ranges of performance. The technique is most useful for cases where the relative importance of goals are unknown at the outset. As in the other two approaches, MEST will consist of two phases namely calculation and decision making phases. The multiobjective problem is modified into a form involving deviational variables as in goal programming. Constraints are added to effectively cut the solution set to the desired "equal suboptimization" level. Mathematical optimization Industrial management Pakorn Adulbhan, Chairperson Sharif, M. N., Examination Committee Techapun Raengkhum, Examination Committee Carl Duisberg Gesellschaft (Germany), Scholarship Donor Asian Institute of Technology. Thesis ; no. 1117 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B23187 .b10367718 mnait x 251208 2 951012 m a x 0 mnait mnarc 20 40 Barcode : 30050003021937 CREATED : 1994-05-17 RECORD # : i10458694 LPATRON : 1015030 LCHKIN : 2002-01-11 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 1 TOT RENEW : 0 Barcode : 30050160088349 CREATED : 2016-04-29 RECORD # : i12964785 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 62003 62003 0 0 0 0 MAIN MAIN mnait 2026-08-18 0 AIT Thesis no. 1117 30050003021937 2026-08-18 14:37:01 1 2026-08-18 20 0 0 0 0 MAIN MAIN mnarc 2026-08-18 0 AIT Thesis no. 1117 30050160088349 2026-08-18 14:37:01 2026-08-18 40