The dynamic programming approach to the multicriterion optimization problem.
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Authors
Kim, Kwang Bog
Subjects
multicriterion optimization problem
multiple return function
multiple aggregate return function
nondominated solution
decomposition
multiple return function
multiple aggregate return function
nondominated solution
decomposition
Advisors
Hartman, James K.
Date of Issue
1978-03
Date
March 1978
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Decision makers are often confronted with problems for which there
exist several distinct measures of success. Such problems can often
be expressed in terms of linear or nonlinear programming models with
several "criterion" functions instead of single objective functions.
A variety of techniques have been applied to multicriterion problems,
but the approach used here, "The Dynamic Programming Approach to Multicriterion
Optimization Problem," is based on the concept that the ideal
solution to a multiobjective problem must be a pareto optimal solution.
In many cases simply narrowing the set of candidate solutions to the
set of all pareto optimal solutions may enable the decision maker to
find the compromise being sought. The determination of nondominated
points and corresponding nondominated values (pareto optimal solution)
related to the multicriterion optimization problem is approached through
the use of dynamic programming. The dynamic programming approach has an
attractive property which provides the basis for generation of nondominated
solutions at each stage by the decomposition method. By
using recursive equations we can find out the nondominated points and
corresponding nondominated solutions of multiaggregate return function.
Type
Thesis
Description
Series/Report No
Department
Operations Research
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Copyright is reserved by the copyright owner