Integrating reference point, Kuhn–Tucker conditions and neural network approach for multi-objective and multi-level programming problems

In this paper, a neural network approach is constructed to solve multi-objective programming problem (MOPP) and multi-level programming problem (MLPP). The main idea is to convert the MOPP and the MLPP into an equivalent convex optimization problem. A neural network approach is then constructed for...

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Vydáno v:	Opsearch Ročník 54; číslo 4; s. 663 - 683
Hlavní autoři:	Rizk-Allah, R. M., Abo-Sinna, Mahmoud A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New Delhi Springer India 01.12.2017 Springer Nature B.V
Témata:	Application Article Business and Management Computer simulation Convexity Kuhn-Tucker method Management Mathematical programming Mathematics Multiple objective analysis Neural networks Operations research Operations Research/Decision Theory Optimization Simulation Multi-level programming Asymptotic stability Multi-objective programming Neural network Karush–Kuhn–Tucker conditions
ISSN:	0030-3887, 0975-0320
On-line přístup:	Získat plný text
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