A Combined Local-Global Active Set Strategy for Nonlinear Design Optimization

1988 ◽  
Vol 110 (4) ◽  
pp. 464-471 ◽  
Author(s):  
Heng Long Li ◽  
P. Y. Papalambros
Keyword(s):  
Gradient Algorithm ◽  
Global Knowledge ◽  
Active Set ◽  
Rule Based ◽  
Active Set Strategy ◽  
Nonlinear Design ◽  
Reduced Gradient ◽  
And Performance ◽  
Combined Strategy ◽  
Global Strategies

Local and global knowledge in rule-based forms is combined in an active set strategy for nonlinear programming design models. The combined strategy is implemented with a reduced gradient algorithm for solution of the equality constrained sub-problem. The strategy unifies previously separate local and global strategies. Algorithmic implementation and performance are discussed together with examples. This article is a sequel to a previous one describing a linear programming application of the strategy.

A Combined Local-Global Active Set Strategy for Nonlinear Design Optimization

1987 ◽  
Author(s):  
Heng Long Li ◽  
P. Y. Papalambros
Keyword(s):  
Gradient Algorithm ◽  
Global Knowledge ◽  
Active Set ◽  
Rule Based ◽  
Active Set Strategy ◽  
Nonlinear Design ◽  
Reduced Gradient ◽  
And Performance ◽  
Combined Strategy ◽  
Global Strategies

Abstract Local and global knowledge in rule-based forms is combined in an active set strategy for nonlinear programming design models. The combined strategy is implemented with a reduced gradient algorithm for solution of the equality constrained subproblem. The strategy unifies previously separate local and global strategies. Algorithmic implementation and performance are discussed together with examples. This article is a sequel to a previous one describing a linear programming application of the strategy.

An Interior Linear Programming Algorithm Using Local and Global Knowledge

1988 ◽  
Vol 110 (1) ◽  
pp. 58-64 ◽  
Author(s):  
Heng Long Li ◽  
Panos Papalambros
Keyword(s):  
Linear Programming ◽  
Nonlinear Programming ◽  
Programming Algorithm ◽  
Global Knowledge ◽  
Active Set ◽  
Active Set Strategy ◽  
Linear Programming Algorithm ◽  
Linear Programming Problems

A new algorithm for linear programming problems is presented. The algorithm makes interior moves with a special active set strategy that utilizes both local and global knowledge. This knowledge represents primarily monotonicity and dominance information. The article describes the rationale, theory, implementation, and some test examples for the algorithm. The ideas presented form the basis for nonlinear programming extensions in sequel articles.

An Active Set Sequential Linearization Algorithm for Nonlinear Design Optimization

1987 ◽  
Author(s):  
N. Tzannetakis ◽  
P. Y. Papalambros
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Programming Algorithm ◽  
Linear Programs ◽  
Chemical Process Design ◽  
Active Set ◽  
Active Set Strategy ◽  
Nonlinear Design ◽  
Working Set ◽  
Sequential Linearization

Abstract Solution of nonlinear design optimization problems via a sequence of linear programs is regaining attention for solving certain model classes, such as in structural design and chemical process design. An active set strategy modification of an algorithm by Palacios-Gomez is presented. A special interior linear programming algorithm with active set strategy is used also for solving the subproblem and generating the working set of the outer iterations. Examples are included.

A Case for a Knowledge-Based Active Set Strategy

1984 ◽  
Vol 106 (1) ◽  
pp. 77-81 ◽  
Author(s):  
S. Azarm ◽  
P. Papalambros
Keyword(s):  
Design Optimization ◽  
Global Knowledge ◽  
Active Set ◽  
Optimization Program ◽  
Active Set Strategy ◽  
Active Constraints ◽  
Knowledge Based ◽  
The One ◽  
Monotonicity Analysis

A strategy for selecting active constraints in a design optimization program is proposed. The strategy differs from previous ones in that it suggests a combination of local and global knowledge. This knowledge may be analytical in nature, such as the one provided by monotonicity analysis. But it may also be provided by an expert. The strategy is proposed as a first attempt toward development of knowledge-based iteration procedures for optimization.

Active set strategy of optimized extreme learning machine

2014 ◽  
Vol 59 (31) ◽  
pp. 4152-4160 ◽  
Author(s):  
Xiao-Jian Ding ◽  
Bao-Fang Chang
Keyword(s):  
Extreme Learning Machine ◽  
Active Set ◽  
Active Set Strategy ◽  
Learning Machine

Optimal Design of Semisubmersible’s Form Based on Systems Analysis

1984 ◽  
Vol 106 (4) ◽  
pp. 524-530 ◽  
Author(s):  
S. Akagi ◽  
R. Yokoyama ◽  
K. Ito
Keyword(s):  
Optimal Design ◽  
Computer Aided Design ◽  
Optimization Problem ◽  
Design Method ◽  
Gradient Algorithm ◽  
Interpretive Structural Modeling ◽  
Reduced Gradient ◽  
Optimal Design Method ◽  
Generalized Reduced Gradient ◽  
Aided Design

With the objective of developing a computer-aided design method to seek the optimal semisubmersible’s form, hierarchical relationships among many design objectives and conditions are investigated first based on the interpretive structural modeling method. Then, an optimal design method is formulated as a nonlinear multiobjective optimization problem by adopting three mutually conflicting design objectives. A set of Pareto optimal solutions is derived numerically by adopting the generalized reduced gradient algorithm, and it is ascertained that the designer can determine the optimal form more rationally by investigating the trade-off relationships among design objectives.

A model for fi nding the optimal routes for a combined route container train

Innotrans ◽  
2021 ◽  
pp. 15-21
Author(s):  
Chang Hao ◽  
◽  
Daria Ivanovna Kochneva ◽  
Keyword(s):  
Software Implementation ◽  
Gradient Algorithm ◽  
Rolling Stock ◽  
Optimal Route ◽  
Delivery Time ◽  
Container Transportation ◽  
Cargo Handling ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient ◽  
Train Loading

The article is devoted to the development of the model for finding an optimal route for a combined route container train (CRCT), i.e. a train with a designated route and schedule, en route from the initial to the final station without reforming of a rolling stock, but carrying out cargo handling operations for loading/unloading containers at intermediate stops of the route. It is proposed to call the optimal route of a CRCT, which provides the minimum delivery time while ensuring the targeted train loading on each section and with a set value of demand for container transportation at each point of the route. A software implementation of the model in the MS Excel environment is proposed using the built-in generalized reduced gradient algorithm.

Implementation of Semi-Heuristic Reasoning for Boundedness Analysis of Design Optimization Models

1987 ◽  
Author(s):  
J. R. J. Rao ◽  
P. Y. Papalambros
Keyword(s):  
Optimal Design ◽  
Heuristic Search ◽  
Optimization Models ◽  
Programming Environment ◽  
Initial Model ◽  
Active Set ◽  
Design Models ◽  
Active Set Strategy ◽  
Reasoning System ◽  
Global Boundedness

Abstract A production system performing global boundedness analysis of optimal design models has been implemented in the OPS5 programming environment. The system receives as input an initial model monotonicity table and derives global facts about boundedness and constraint activity using monotonicity principles. Additional facts may be discovered by heuristic search of implicit elimination sequences that examine boundedness of reduced models with active constraints eliminated. The global facts generated automatically by this reasoning system can be used either for a global solution, or for a combined local-global active set strategy.

Sign in / Sign up

Export Citation Format

Share Document