On solving constrained optimization problems with neural networks: a penalty method approach

1993 ◽  
Vol 4 (6) ◽  
pp. 931-940 ◽  
Author(s):  
W.E. Lillo ◽  
M.H. Loh ◽  
S. Hui ◽  
S.H. Zak
Author(s):  
Christian Kanzow ◽  
Andreas B. Raharja ◽  
Alexandra Schwartz

AbstractA reformulation of cardinality-constrained optimization problems into continuous nonlinear optimization problems with an orthogonality-type constraint has gained some popularity during the last few years. Due to the special structure of the constraints, the reformulation violates many standard assumptions and therefore is often solved using specialized algorithms. In contrast to this, we investigate the viability of using a standard safeguarded multiplier penalty method without any problem-tailored modifications to solve the reformulated problem. We prove global convergence towards an (essentially strongly) stationary point under a suitable problem-tailored quasinormality constraint qualification. Numerical experiments illustrating the performance of the method in comparison to regularization-based approaches are provided.


2020 ◽  
Author(s):  
Giovanni Iacovelli ◽  
Claudio Iacovelli

In this work, the existence of a correspondence between fundamental programming language control structures and mathematical formulation is proven. The proposed interpretation is given through a well-defined logical circuit analytical expression. Relevant geometrical applications having wide implications in engineering branches are presented together with a new Penalty Method for constrained optimization problems handling.


2013 ◽  
Vol 303-306 ◽  
pp. 1519-1523 ◽  
Author(s):  
Ming Gang Dong ◽  
Xiao Hui Cheng ◽  
Qin Zhou Niu

To solve constrained optimization problems, an Oracle penalty method-based comprehensive learning particle swarm optimization (OBCLPSO) algorithm was proposed. First, original Oracle penalty was modified. Secondly, the modified Oracle penalty method was combine with comprehensive learning particle swarm optimization algorithm. Finally, experimental results and comparisons were given to demonstrate the optimization performances of OBCLPSO. The results show that the proposed algorithm is a very competitive approach for constrained optimization problems.


2020 ◽  
Author(s):  
Giovanni Iacovelli ◽  
Claudio Iacovelli

In this work, the existence of a correspondence between fundamental programming language control structures and mathematical formulation is proven. The proposed interpretation is given through a well-defined logical circuit analytical expression. Relevant geometrical applications having wide implications in engineering branches are presented together with a new Penalty Method for constrained optimization problems handling.


2020 ◽  
Author(s):  
Giovanni Iacovelli ◽  
Claudio Iacovelli

In this work, the existence of a correspondence between fundamental programming language control structures and mathematical formulation is proven. The proposed interpretation is given through a well-defined logical circuit analytical expression. Relevant geometrical applications having wide implications in engineering branches are presented together with a new Penalty Method for constrained optimization problems handling.


Sign in / Sign up

Export Citation Format

Share Document