On some experiments which delimit the utility of nonlinear programming methods for engineering design

1982 ◽  
pp. 118-136 ◽  
Author(s):  
E. Sandgren ◽  
K. M. Ragsdell
Keyword(s):  
Nonlinear Programming ◽  
Engineering Design ◽  
Nonlinear Programming Methods

scholarly journals A QFD-Based Quality and Capability Design Method for Transboundary Services

2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Chao Ma ◽  
Wei Dong Liu ◽  
Zhi Ying Tu ◽  
Zhong Jie Wang ◽  
Xiao Fei Xu
Keyword(s):  
Nonlinear Programming ◽  
Quality Function Deployment ◽  
Design Method ◽  
Quality Parameters ◽  
Optimal Configuration ◽  
Two Phase ◽  
Internet Service ◽  
Fuzzy Nonlinear Programming ◽  
Nonlinear Programming Methods ◽  
Multiple Domains

The “transboundary”, an emerging phenomenon in the Internet service ecosystem, is leading to the flourishing of innovative services. A transboundary service incorporates services, resources, and technologies from multiple domains into its business to create a particular competitive advantage and unique user experiences. It is difficult to comprehensively consider all the constraints from multiple domains to precisely design the nonfunctional characteristics of transboundary services, such as quality attributes and capability attributes. We propose a two-phase quality design method for transboundary services called value quality deployment-quality capability deployment (VQD-QCD) based on quality function deployment (QFD). Given the restrictions of transboundary services, VQD-QCD translates the value expectations of multiple stakeholders into an optimal configuration for global quality parameters (GQPs), local quality parameters, and capability parameters. Details of VQD are illustrated. Considering the inherent vagueness and uncertainty of relationships between value expectations and GQPs, and among GQPs, fuzzy least absolute regression and fuzzy nonlinear programming methods are incorporated into QFD to identify the quantitative relations between value indicators and GQPs, and among GQPs, and obtain an optimal configuration scheme for GQPs. Usability of the proposed method is validated through a case study on the “DiDi mobile transportation service”, which is a representative transboundary service in China. Compared with the current method, which is inaccurate and inefficient because its translation between value expectations and relevant quality and capability parameters is artificial and subjective, the proposed method integrates fuzzy least absolute regression and fuzzy nonlinear programming methods into QFD, which facilitate transboundary service designers to precisely and efficiently design the quality and capability characteristics of innovative services in the manner of semiautomatisation, which promotes the innovative design of transboundary services.

Design of survey systems using nonlinear programming methods

1972 ◽  
Vol 103 (1) ◽  
pp. 31-45 ◽  
Author(s):  
CPT Clifford W. Greve
Keyword(s):  
Nonlinear Programming ◽  
Nonlinear Programming Methods

Nonlinear Mixed Integer-Discrete-Continuous Programming and its Application to Engineering Design Problems

1989 ◽  
Author(s):  
J.-F. Fu ◽  
R. G. Fenton ◽  
W. L. Cleghorn
Keyword(s):  
Nonlinear Programming ◽  
Objective Function ◽  
Engineering Design ◽  
Optimization Algorithm ◽  
Mixed Integer ◽  
Continuous Variables ◽  
Design Problems ◽  
Continuous Programming ◽  
Engineering Design Problems ◽  
Standard Values

Abstract An algorithm for solving nonlinear programming problems containing integer, discrete and continuous variables is presented. Based on a commonly employed optimization algorithm, penalties on integer and/or discrete violations are imposed on the objective function to force the search to converge onto standard values. Examples are included to illustrate the practical use of this algorithm.

Iterative Fixture Layout and Clamping Force Optimization Using the Genetic Algorithm

2001 ◽  
Vol 124 (1) ◽  
pp. 119-125 ◽  
Author(s):  
Krishnakumar Kulankara ◽  
Srinath Satyanarayana ◽  
Shreyes N. Melkote
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Programming ◽  
Primary Objective ◽  
Fixture Design ◽  
Clamping Force ◽  
Optimal Solutions ◽  
Fixture Layout ◽  
Force Optimization ◽  
Nonlinear Programming Methods ◽  
Objective Being

Fixture design is a critical step in machining. An important aspect of fixture design is the optimization of the fixture, the primary objective being the minimization of workpiece deflection by suitably varying the layout of fixture elements and the clamping forces. Previous methods for fixture design optimization have treated fixture layout and clamping force optimization independently and/or used nonlinear programming methods that yield sub-optimal solutions. This paper deals with application of the genetic algorithm (GA) for fixture layout and clamping force optimization for a compliant workpiece. An iterative algorithm that minimizes the workpiece elastic deformation for the entire cutting process by alternatively varying the fixture layout and clamping force is proposed. It is shown via an example of milling fixture design that this algorithm yields a design that is superior to the result obtained from either fixture layout or clamping force optimization alone.

Nonlinear programming methods and network flows

1994 ◽  
Vol 30 (6) ◽  
pp. 846-854 ◽  
Author(s):  
B. N. Pshenichnyi ◽  
E. E. Kirik
Keyword(s):  
Nonlinear Programming ◽  
Network Flows ◽  
Nonlinear Programming Methods
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