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== Solution concepts ==
A feasible point <math>x</math> is called ''efficient'' if there is no feasible point <math>y</math> with <math>Px \leq Py</math>, <math>Px \neq Py</math>, where <math>\leq</math>
Often in the literature, the aim in multiple objective linear programming is to compute the set of all efficient extremal points <ref name="EckerKouada1978">{{cite journal|last1=Ecker|first1=J. G.|last2=Kouada|first2=I. A.|title=Finding all efficient extreme points for multiple objective linear programs|journal=Mathematical Programming|volume=14|issue=1|year=1978|pages=249–261|issn=0025-5610|doi=10.1007/BF01588968}}</ref>. There are also algorithms to determine the set of all maximal efficient faces <ref name="EckerHegner1980">{{cite journal|last1=Ecker|first1=J. G.|last2=Hegner|first2=N. S.|last3=Kouada|first3=I. A.|title=Generating all maximal efficient faces for multiple objective linear programs|journal=Journal of Optimization Theory and Applications|volume=30|issue=3|year=1980|pages=353–381|issn=0022-3239|doi=10.1007/BF00935493}}</ref>. Based on these goals, the set of all efficient (extreme) points can seen to be the solution of MOLP. This type of solution concept is called ''decision set based''<ref name="Benson1998">{{cite journal|title=An outer approximation algorithm for generating all efficient extreme points in the outcome set of a multiple objective linear programming problem|last1=Benson|first1=Harold P.|journal=Journal of Global Optimization|volume=13|issue=1|year=1998|pages=1–24|issn=09255001|doi=10.1023/A:1008215702611}}</ref>. It is not compatible with an optimal solution of a linear program but rather parallels the set of all optimal solutions of a linear program (which is more difficult to determine).
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