Computational experience with penalty-barrier methods for nonlinear programming

被引:28
|
作者
Breitfeld, MG
Shanno, DF
机构
[1] RUTGERS STATE UNIV, RUTCOR, NEW BRUNSWICK, NJ 08903 USA
[2] RUTGERS STATE UNIV, GRAD SCH MANAGEMENT, NEW BRUNSWICK, NJ 08903 USA
[3] RUTGERS STATE UNIV, RUTGERS CTR OPERAT RES, NEW BRUNSWICK, NJ 08903 USA
关键词
D O I
10.1007/BF02206826
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
It was recently shown that modified barrier methods are not only theoretically but also computationally superior to classic barrier methods when applied to general nonlinear problems. In this paper, a penalty-barrier function is presented that was designed to overcome particular problems associated with modified log-barrier functions. A quadratic extrapolation of logarithmic terms as well as handling simple bounds separately are utilized. The resulting penalty-barrier method is outlined and compared to previous methods. The conclusion drawn from the computational tests is that the revised method exhibits superior performance on the test set of this study and consequently holds promise as a viable technique for general nonlinear programming.
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页码:439 / 463
页数:25
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