AI SearchSolving multicriterion nonlinear separable programming problems
Call Number: AIT Thesis no. 1153 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. 1153Publication details: Bangkok : Asian Institute of Technology, 1976Description: 159 pSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1976 Summary: This research describes five solution techniques for nonlinear separable programming problems with multiple objective functions. The utilization of separable programming made possible the application of these solution techniques by transforming the multi-objective nonlinear problem into its equivalent linear programming problem using polygonal approximation. The solution procedures include a goal programming technique and four interactive approaches, two of which are the modified STEP method and the BELENSON-KAPUR algorithm for linear programming problems and two methods using rational relaxation of objective functions by certain per cent of their optimal values. The performance of these methods for multicriterion nonlinear optimization were evaluated and analyzed.
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20-AIT Publication
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Asian Institute of Technology Library AIT Publications | AIT Thesis no. 1153 (Browse shelf(Opens below)) | 3 | Available | 30050003022828 | |||||||||||||
40-Archives
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Asian Institute of Technology Library Archives | AIT Thesis no. 1153 (Browse shelf(Opens below)) | Available | 30050160088091 |
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, 1976
This research describes five solution techniques for nonlinear separable programming problems with multiple objective functions. The utilization of separable programming made possible the application of these solution techniques by transforming the multi-objective nonlinear problem into its equivalent linear programming problem using polygonal approximation. The solution procedures include a goal programming technique and four interactive approaches, two of which are the modified STEP method and the BELENSON-KAPUR algorithm for linear programming problems and two methods using rational relaxation of objective functions by certain per cent of their optimal values. The performance of these methods for multicriterion nonlinear optimization were evaluated and analyzed.
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