scholarly journals Computational Implementation and Tests of a Sequential Linearization Algorithm for Mixed-Discrete Nonlinear Design Optimization

1991 ◽  
Vol 113 (3) ◽  
pp. 335-345 ◽  
Author(s):  
Han Tong Loh ◽  
P. Y. Papalambros
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Theoretical Background ◽  
Test Problems ◽  
Computational Results ◽  
Sample Design ◽  
Design Problems ◽  
Nonlinear Design ◽  
Computational Implementation ◽  
Sequential Linearization

A previous article gave the theoretical background and motivation for a new sequential linearization approach to the solution of mixed-discrete nonlinear optimal design problems. The present sequel article gives the implementation details of program MINSLIP based on this approach. Illustrative examples, modeling issues, and program parameter selection are discussed. A report on extensive computational results with test problems, as well as comparisons with other methods, shows advantages in both robustness and efficiency. Sample design applications are included.

scholarly journals Computational Implementation and Tests of a Sequential Linearization Algorithm for Mixed-Discrete Nonlinear Design Optimization

1990 ◽  
Author(s):  
Han Tong Loh ◽  
Panos Y. Papalambros
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Theoretical Background ◽  
Test Problems ◽  
Computational Results ◽  
Sample Design ◽  
Design Problems ◽  
Nonlinear Design ◽  
Computational Implementation ◽  
Sequential Linearization

Abstract A previous article gave the theoretical background and motivation for a new sequential linearization approach to the solution of mixed-discrete nonlinear optimal design problems. The present sequel article gives the implementation details of program MINSLIP based on this approach. Illustrative examples, modeling issues, and program parameter selection are discussed. A report on extensive computational results with test problems, as well as comparisons with other methods, shows advantages in both robustness and efficiency. Sample design applications are included.

scholarly journals A Sequential Linearization Approach for Solving Mixed-Discrete Nonlinear Design Optimization Problems

1991 ◽  
Vol 113 (3) ◽  
pp. 325-334 ◽  
Author(s):  
Han Tong Loh ◽  
P. Y. Papalambros
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Continuous Variables ◽  
New Approach ◽  
Design Variables ◽  
Nonlinear Design ◽  
Discrete Problems ◽  
Computationally Intensive ◽  
Discrete Values ◽  
Sequential Linearization

Design optimization models of often contain variables that must take only discrete values, such as standard sizes. Nonlinear optimization problems with a mixture of discrete and continuous variables are very difficult, and existing algorithms are either computationally intensive or applicable to models with special structure. A new approach for solving nonlinear mixed-discrete problems with no particular structure is presented here, motivated by its efficiency for models with extensive monotonicities of the problem’s objective and constraint functions with respect to the design variables. It involves solving a sequence of mixed-discrete linear approximations of the original nonlinear model. In this article, a review of previous approaches is followed by description of the resulting algorithm, its convergence properties and limitations. Several illustrative examples are given. A sequel article presents a detailed algorithmic implementation and extensive computational results.

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.

scholarly journals A Sequential Linearization Approach for Solving Mixed-Discrete Nonlinear Design Optimization Problems

1990 ◽  
Author(s):  
Han Tong Loh ◽  
Panos Y. Papalambros
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Continuous Variables ◽  
New Approach ◽  
Design Variables ◽  
Nonlinear Design ◽  
Discrete Problems ◽  
Computationally Intensive ◽  
Discrete Values ◽  
Sequential Linearization

Abstract Design optimization models often contain variables that must take only discrete values, such as standard sizes. Nonlinear optimization problems with a mixture of discrete and continuous variables are very difficult, and existing algorithms are either computationally intensive or applicable to models with special structure. A new approach for solving nonlinear mixed-discrete problems with no particular structure is presented here, motivated by its efficiency for models with extensive monotonicities of the problem’s objective and constraint functions with respect to the design variables. It involves solving a sequence of mixed-discrete linear approximations of the original nonlinear model. In this article, a review of previous approaches is followed by description of the resulting algorithm, its convergence properties and limitations. Several illustrative examples are given. A sequel article presents a detailed algorithmic implementation and extensive computational results.

Optimal design of mechanical components using the Bees Algorithm

2008 ◽  
Vol 223 (5) ◽  
pp. 1051-1056 ◽  
Author(s):  
D T Pham ◽  
A Ghanbarzadeh ◽  
S Otri ◽  
E Koç
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Honey Bees ◽  
Mechanical Design ◽  
Optimization Techniques ◽  
Bees Algorithm ◽  
Search Procedure ◽  
Robust Performance ◽  
Beam Structure ◽  
Design Problems

This paper describes the first application of the Bees Algorithm to mechanical design optimization. The Bees Algorithm is a search procedure inspired by the way honey bees forage for food. Two standard mechanical design problems, the design of a welded beam structure and the design of coil springs, were used to benchmark the Bees Algorithm against other optimization techniques. The paper presents the results obtained showing the robust performance of the Bees Algorithm.

Shape-design optimization of hull structures considering thermal deformation

2013 ◽  
Vol 228 (13) ◽  
pp. 2266-2277
Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Thermal Deformation ◽  
Parametric Design ◽  
Optimization Method ◽  
Optimization Process ◽  
Design Parameters ◽  
Shape Design ◽  
Shape Design Optimization ◽  
Modified Method

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.

Foraging-Directed Adaptive Linear Programming: An Algorithm for Solving Nonlinear Mixed Discrete/Continuous Design Problems

1996 ◽  
Author(s):  
Kemper Lewis ◽  
Farrokh Mistree
Keyword(s):  
Linear Programming ◽  
Continuous Variables ◽  
Design Problems ◽  
Design Studies ◽  
Design Models ◽  
Sequential Linearization ◽  
And Behavior

Abstract Design models often contain a combination of discrete, integer, and continuous variables. Previously, the Adaptive Linear Programming (ALP) Algorithm, which is based on sequential linearization, has been used to solve design models composed of continuous and Boolean variables. In this paper, we extend the ALP Algorithm using a discrete heuristic based on the analogy of an animal foraging for food. This algorithm for mixed discrete/continuous design problems integrates ALP and the foraging search and is called Foraging-directed Adaptive Linear Programming (FALP). Two design studies are presented to illustrate the effectiveness and behavior of the algorithm.

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