Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming

作     者：Lasdon, L.S. Waren, A.D. Jain, A. Ratner, M. 

作者机构：Department of General Business School of Business Administration University of Texas Austin TX 78712 United States Department of Computer and Information Science Cleveland State University Cleveland OH 44115 United States Energy Systems Group Stanford Research Institute Menlo Park CA 94025 United States Department of Systems and Computer Science Case Western Reserve University Cleveland OH 44106 United States 

出 版 物：《ACM Transactions on Mathematical Software (TOMS)》 (ACM Trans. Math. Softw.)

年 卷 期：1978年第4卷第1期

页      面：34-50页

学科分类：08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：constrained optimization gradient algorithm GRG mathematical programming nonlinear programming optimization reduced gradient software engineering 

摘      要：An algorithm for solving nonlinear optimization problems is described along with its implementation as a Fortran program. Computational results are provided which compare its performance with that of other algorithms. The generalized reduced gradient (GRG) algorithm used is a nonlinear extension of the simplex method for linear programming. It is shown thatthe implementation is both robust and efficient. © 1978, ACM. All rights reserved.