A method of multipliers for mathematical programming problems with equality and inequality constraints

1975 ◽  
Vol 17 (1-2) ◽  
pp. 155-161 ◽  
Author(s):  
S. B. Schuldt
Keyword(s):  
Mathematical Programming ◽  
Inequality Constraints ◽  
Method Of Multipliers ◽  
Equality And Inequality Constraints ◽  
Mathematical Programming Problems

scholarly journals Lagrange duality and saddle point optimality conditions for semi-infinite mathematical programming problems with equilibrium constraints

2019 ◽  
Vol 29 (4) ◽  
pp. 433-448
Author(s):  
Kunwar Singh ◽  
J.K. Maurya ◽  
S.K. Mishra
Keyword(s):  
Mathematical Programming ◽  
Saddle Point ◽  
Optimality Conditions ◽  
Optimization Problems ◽  
Inequality Constraints ◽  
Mathematical Programming Problem ◽  
Dual Model ◽  
Equilibrium Constraints ◽  
Convexity Assumptions ◽  
Mathematical Programming Problems

In this paper, we consider a special class of optimization problems which contains infinitely many inequality constraints and finitely many complementarity constraints known as the semi-infinite mathematical programming problem with equilibrium constraints (SIMPEC). We propose Lagrange type dual model for the SIMPEC and obtain their duality results using convexity assumptions. Further, we discuss the saddle point optimality conditions for the SIMPEC. Some examples are given to illustrate the obtained results.

On the method of multipliers for mathematical programming problems

1972 ◽  
Vol 10 (1) ◽  
pp. 1-33 ◽  
Author(s):  
A. Miele ◽  
P. E. Moseley ◽  
A. V. Levy ◽  
G. M. Coggins
Keyword(s):  
Mathematical Programming ◽  
Method Of Multipliers ◽  
Mathematical Programming Problems

Computer-Aided Synthesis of Mechanisms Using Nonlinear Programming

1973 ◽  
Vol 95 (1) ◽  
pp. 339-344 ◽  
Author(s):  
V. K. Gupta
Keyword(s):  
Nonlinear Programming ◽  
Mathematical Programming ◽  
Penalty Function ◽  
Inequality Constraints ◽  
Mathematical Programming Problem ◽  
Spatial Mechanisms ◽  
Synthesis Of Mechanisms ◽  
Computer Aided ◽  
Equality And Inequality Constraints ◽  
Penalty Function Approach

The synthesis of spatial mechanisms is formulated as a mathematical programming problem and solved using a penalty function approach. The objective function as well as the equality and inequality constraints are determined explicitly from conditions such as those required for linkage closure, mobility, and transmissibility.

Computerized Selection of Optimum Machining Conditions for a Job Requiring Multiple Operations

1978 ◽  
Vol 100 (3) ◽  
pp. 356-362 ◽  
Author(s):  
S. S. Rao ◽  
S. K. Hati
Keyword(s):  
Nonlinear Programming ◽  
Mathematical Programming ◽  
Machine Tools ◽  
Machining Conditions ◽  
Coupling Constraints ◽  
Programming Techniques ◽  
Mathematical Programming Problems ◽  
The Individual ◽  
The Cost ◽  
Selection Of

The problem of determining the optimum machining conditions for a job requiring multiple operations has been investigated. Three objectives, namely, the minimization of the cost of production per piece, the maximization of the production rate and, the maximization of the profit are considered in this work. In addition to the usual constraints that arise from the individual machine tools, some coupling constraints have been included in the formulation. The problems are formulated as standard mathematical programming problems, and nonlinear programming techniques are used to solve the problems.

Sign in / Sign up

Export Citation Format

Share Document