The computer technologies of machine learning and multiobjective optimization were introduced to develop the catalyst for fluid catalytic cracking (FCC). Response surface methodology was applied a training set consisting 1000 data points with varied compositions which consist variety catalysts compositions, feedstock properties, pseudo-equilibrium conditions, performance test conditions as inpu...

This paper reviews the multiobjective fitness evaluation method called Energy Minimization (Zebulum et al, 1998a; Zebulum et al, 1998b; Zebulum et al, 2000a), and presents an analysis of the method's behavior when used in a genetic algorithm applied to production scheduling of a petroleum refinery. The experimental results are presented and analyzed, leading to an overall evaluation of the bene...

Multiobjective Pareto optimal solutions for epoxy semi-batch polymerization process are obtained by adapting nondominated sorting genetic algorithm II (NSGA II). The objective is to produce polymer of maximum possible number average molecular weight (Mn) with a specified value of polydispersity index (PDI) and number average molecular weight in minimum possible time. The M and reaction time a p...

A multiobjective genetic algorithm (GA) is introduced to identify both the neighborhood and the rule set in the form of a parsimonious Boolean expression for both one- and two-dimensional cellular automata (CA). Simulation results illustrate that the new algorithm performs well even when the patterns are corrupted by static and dynamic noise.

In this paper, three evolutionary algorithms have been discussed for solving three-criteria optimization problem of finding a set of Pareto-optimal program module assignments. An adaptive evolutionary algorithm has been recommended for solving an established multiobjective optimization problem. Moreover, a multi-criterion genetic algorithm and an evolution strategy have been considered. Some nu...

A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative...

Because there is no generally accepted metric for measuring the performance of anaphora resolution systems, a combination of metrics was proposed to evaluate submissions to the 2011 CONLL Shared Task (Pradhan et al., 2011). We investigate therefore Multiobjective function Optimization (MOO) techniques based on Genetic Algorithms to optimize models according to multiple metrics simultaneously.

The paper introduces a novel problem based on causal modeling in marketing where knowledge discovery is able to provide useful results (as shown in a real-world application). The problem features (with uncertain data and available expert knowledge) and the proposed multiobjective optimization approach makes genetic fuzzy systems to be a good framework to deal with that.

It has been previously established that genetic programming can be used as an automated invention machine to synthesize designs for complex structures. In particular, genetic programming has automatically synthesized structures that infringe, improve upon, or duplicate the functionality of 21 previously patented inventions (including six 21-century patented analog electrical circuits) and has a...