Skip to main content
Article thumbnail
Location of Repository

Handling integrated quantitative and qualitative search space in engineering design optimisation problems

By Victor Oduguwa, Ashutosh Tiwari and Rajkumar Roy

Abstract

Since information in engineering design problems can be both quantitative (QT) and qualitative (QL) in nature, combining both types of information can result in more realistic solutions for real world optimisation problems. However, most of the approaches reported in the literature are incapable of conducting optimisation searches in such a mixed environment. Therefore this report proposes a mathematically proven methodology for handling integrated QT and QL search space in real world optimisation problems. The report begins by presenting the definition of these optimisation problems, an analysis of the challenges that they pose for existing optimisation strategies and related research. The report then presents the proposed solution strategy and the mathematical proof. Furthermore, a case study on a rod rolling problem is presented to validate the effectiveness of the proposed methodology. The report concludes with a brief outline of limitations and future research activities

Topics: Design optimisation, Evolutionary computing, Qualitative information, Quantitative information, Search space, Rolling system, DEG Report
Year: 2003
OAI identifier: oai:dspace.lib.cranfield.ac.uk:1826/65
Provided by: Cranfield CERES

Suggested articles

Citations

  1. (2003). (submitted for publication)) An Integrated Design Optimisation approach for Quantitative and Qualitative Search Space. doi
  2. (1975). A comment on Blanning's metamodel for sensitivity analysis: the regression metamodel in simulation. doi
  3. (2000). A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: doi
  4. (1994). A Study on the Rolling of I-Section Beams. doi
  5. (1997). Abo Elkhier doi
  6. (1997). Adaptive Search and the Preliminary Design of Gas Turbine Blade Cooling System, PhD Thesis,
  7. (1998). An evolutionary algorithm for multiobjective optimization: The strength Pareto approach. doi
  8. (1998). Application of Fuzzy Reasoning Techniques for Roll Pass Design Optimisation.
  9. (1997). Application of genetic algorithm to optimal design of the die shape in Extrusion. doi
  10. (1989). Computations with Imprecise Parameters in Engineering Design: Background and Theory. doi
  11. (1970). Decision Making in a Fuzzy Environment. doi
  12. (1997). Design and Analysis of Experiments, doi
  13. (1999). Direct determination of sequences of passes for the strip rolling process by means of fuzzy logic rules. doi
  14. (2001). Evolutionary computing techniques for handling variable interaction in engineering design optimisation,
  15. (2000). Fuzzy algorithm for calculating roll speed variation based on roll separating force in hot rolling. doi
  16. (1996). Fuzzy Fitness Function for Electric machine Design by Genetic Algorithm.
  17. (2003). Fuzzy Multi-Objective Optimisation Approach for Rod Shape Design in Long Product Rolling. Fuzzy Sets and Systems -Handling integrated quantitative and qualitative search space in real world design optimisation doi
  18. (1990). General purpose fem simulator for 3-d rolling.
  19. (1999). Generator maintenance scheduling using genetic algorithm with a fuzzy evaluation function. Fuzzy Sets and Systems doi
  20. (2003). Genetic Algorithm in process optimisation. doi
  21. (1989). Genetic Algorithm in Search, Optimization and Machine Learning. Massachusetts, Addison Wesley. Handling integrated quantitative and qualitative search space in real world design optimisation
  22. (1993). Genetic Algorithms for multiobjective optimization: Formulation, discussion and generalization.
  23. (2003). Global strategy for optimizing textile dyeing manufacturing process via GA-based grey nonlinear integer programming. doi
  24. (1992). Introduction to Linear Regression Analysis. doi
  25. (1979). Methods and applications of interval analysis, doi
  26. (1999). Multiobjective Evolutionary Algorithms: Classifications, Analysis, and New Innovations, PhD Thesis,
  27. (1985). Multiple Objective Optimization with Vector Evaluated Genetic Algorithms.
  28. (2002). Nuttle doi
  29. (1974). On fuzzy mathematical programming. doi
  30. (1974). Optimization in fuzzy environment.
  31. (1983). Probabilistic Engineering Design.
  32. (1996). Process design in multi-stage cold forging by the finite element method. doi
  33. (2002). Process Optimal Design in Forging by Genetic Algorithm. doi
  34. (1983). Ragsdell
  35. (2003). Sensitivity analysis by experimental design and metamodelling: Case study on simulation in national animal disease control. doi
  36. (1996). Some experiences of shape-forming: experiments and numerical simulations. doi
  37. (1986). The Higher Calculus: A History of Real and Complex Analysis from Euler to Weierstrass, doi
  38. (2003). The Optimal Scheduling of a Reversing Strip Mill: Studies Using Multi-population Genetic Algorithms and Differential Evolution. doi
  39. (1999). The Pareto archived evolution strategy: A new baseline algorithm for multiobjective optimisation. doi
  40. (1998). The role of neural networks in the optimisation of rolling processes. doi
  41. (1996). The Simulation Metamodel. doi
  42. (1991). Three-dimensional analysis and computer simulation of shape rolling by the finite and slab element method. doi
  43. (2000). Use of approximation concepts in fuzzy design problems." doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.