Evolutionary normal-boundary intersection (ENBI) method for multi-objective optimization of green sand mould system

  title={Evolutionary normal-boundary intersection (ENBI) method for multi-objective optimization of green sand mould system},
  author={Timothy Ganesan and Irraivan Elamvazuthi and Pandian M. Vasant},
  journal={2011 IEEE International Conference on Control System, Computing and Engineering},
In multi-objective engineering optimization, it is very rare that there exists a unique ideal solution that covers every aspect of the problem. Thus, it is very useful for the decision maker to have multiple options prior to the selection of the best solution. In this work, a novel evolutionary normal boundary intersection (ENBI) method is introduced to identify optimal solutions to the green sand mould system problem. The ENBI method provides a uniform spread of the Pareto frontier in which… 

Figures and Tables from this paper

Multiobjective Optimization of Cement-bonded Sand Mould System with Differential Evolution
In this work, the weighted sum scalarization approach is used in conjunction with the differential evolution (DE) algorithm to construct the approximate Pareto frontier as well as to identify the best solution option.
An Algorithmic Framework for Multiobjective Optimization
This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization and utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms.
A multi-objective approach for resilience-based plant design optimization
ABSTRACT As process plants become more complex, the notion of reliability per se is insufficient to measure stable and cost-effective operations. Recently, the idea of resilience has been put forward
Evaluation of Genetic Algorithm as Learning System in Rigid Space Interpretation
An approach is being adopted that the legitimate theory of GA must be able to explain the learning process (a special case of the successive approximation) of GA, and that learning capability can be used to demonstrate the probable capability of GA to perform beyond the limit cast by the No Free Lunch Theorem.
Hopfield differential evolution for multi-objective optimization of a cement-bonded sand mould system
In this work, the weighted sum scalarization approach was used in conjunction with the Differential Evolution (DE) and the improved Hopfield Differential evolution (Hopf-DE) algorithm to construct the approximate Pareto frontier.
Simulation-based process windows simultaneously considering two and three conflicting criteria in injection molding
The aim is to provide a formal and realistic strategy to set processing conditions in IM operations by considering two and three performance measures in conflict simultaneously through the direct application of the concept of Pareto-dominance in multiple criteria optimization.


Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems
This paper proposes an alternate method for finding several Pareto optimal points for a general nonlinear multicriteria optimization problem that can handle more than two objectives while retaining the computational efficiency of continuation-type algorithms.
Multi-objective optimization of green sand mould system using evolutionary algorithms
In this study, non-linear regression equations developed between the control factors (process parameters) and responses like green compression strength, permeability, hardness and bulk density have been considered for optimization utilizing GA and PSO.
Analysis of the pareto front of a multi-objective optimization problem for a fossil fuel power plant
  • J. H. Van Sickel, P. Venkatesh, K.Y. Lee
  • Environmental Science
    2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century
  • 2008
This paper examines the Pareto front of a simple fossil fuel power plant using a common third-order model. This front is first examined analytically. Then the power plant model is transferred over to
Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
In this paper an extensive, quantitative comparison is presented, applying four multiobjective evolutionary algorithms to an extended 0/1 knapsack problem.
An Investigation of Grinding Process Optimization via Evolutionary Algorithms
Numerical results show that PSO is comparatively superior in comparison with DE and GA algorithms for grinding process optimization in terms of its accuracy and convergent capability.
A fast and elitist multiobjective genetic algorithm: NSGA-II
This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Fault Tolerant Design Using Single and Multicriteria Genetic Algorithm Optimization.
This research shows that a single criterion genetic algorithm can be expected to outperform other methods in efficiency, accuracy, and speed on problems of moderate to high complexity.
Genetic programming - on the programming of computers by means of natural selection
  • J. Koza
  • Computer Science
    Complex adaptive systems
  • 1993
This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.