AI SearchPost-optimality analysis of goal programming problems
Call Number: AIT Thesis no. 1149 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. 1149Publication details: Bangkok : Asian Institute of Technology, 1975Description: 66 pSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1975 Summary: This research work presents some methodologies for post optimality analysis of goal programming problems. Two types of changes in parameters of goal programming problems have bee considered for this purpose - (i) Single change in parameters; (ii) Systematic changes in parameters. For single change, sensitivity analysis of linear programm ing problems has been extended to deal with changes in three different parameters of goal programming problems. These are: (i) ranking of priority, (ii) target, and (iii) coefficient of goal equation. Parametric linear programming has also been extended to deal with systematic changes in targets of goal programming problems. This algorithm helps to find different sets of optimal solutions for different ranges of targets. Finally, illustrative examples on all possible conditions of single and systematic changes in parameters have been presented.
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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, 1975
This research work presents some methodologies for post optimality analysis of goal programming problems. Two types of changes in parameters of goal programming problems have bee considered for this purpose - (i) Single change in parameters; (ii) Systematic changes in parameters. For single change, sensitivity analysis of linear programm ing problems has been extended to deal with changes in three different parameters of goal programming problems. These are: (i) ranking of priority, (ii) target, and (iii) coefficient of goal equation. Parametric linear programming has also been extended to deal with systematic changes in targets of goal programming problems. This algorithm helps to find different sets of optimal solutions for different ranges of targets. Finally, illustrative examples on all possible conditions of single and systematic changes in parameters have been presented.
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