A multi-objective evolutionary approach for fuzzy optimization in production planning

Authors:
F. Jiménez;G. Sánchez;P. Vasant
Affiliations:
Department Ingeniería de la Información y las Comunicaciones, Facultad de Informática, Universidad de Murcia, Murcia, Spain;Department Ingeniería de la Información y las Comunicaciones, Facultad de Informática, Universidad de Murcia, Murcia, Spain;Universiti Teknologi Petronas, Malaysia
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2013

Citing 17
Cited 0

On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds

Mathematical Programming: Series A and B
A general approach to solving a wide class of fuzzy optimization problems

Fuzzy Sets and Systems
A differential equation approach to fuzzy non-linear programming problems

Fuzzy Sets and Systems
Evolutionary Algorithms: The Role of Mutation and Recombination

Evolutionary Algorithms: The Role of Mutation and Recombination
Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems

Evolutionary Algorithms for Solving Multi-Objective Problems
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II

PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Why Use Elitism And Sharing In A Multi-objective Genetic Algorithm?

GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
On the Effects of Archiving, Elitism, and Density Based Selection in Evolutionary Multi-objective Optimization

EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations

Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
An evolutionary algorithm for constrained multi-objective optimization

CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Pareto-optimal solutions in fuzzy multi-objective linear programming

Fuzzy Sets and Systems
The use of parametric programming in fuzzy linear programming

Fuzzy Sets and Systems
An interactive fuzzy satisfying method for multiobjective nonlinear integer programming problems through genetic algorithms

IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Performance assessment of multiobjective optimizers: an analysis and review

IEEE Transactions on Evolutionary Computation
Satisficing solutions of multi-objective fuzzy optimization problems using genetic algorithm

Applied Soft Computing
Multi-objective optimization problems with Fuzzy relation equation constraints regarding max-average composition

Mathematical and Computer Modelling: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we propose a multi-objective optimization approach to solve nonlinear fuzzy optimization problems. Solutions in the Pareto front correspond with the fuzzy solution of the former fuzzy problem expressed in terms of the group of three parameters x*, μ, α, i.e., optimal solution-degree of satisfaction-vagueness factor. The decision maker could choose, in a posteriori decision environment, the most convenient optimal solution according to his degree of satisfaction and vagueness factor. Additionally, an ad-hoc Pareto-based multi-objective evolutionary algorithm, ENORA-II, is proposed and validated in a production planning optimization environment. A real-world industrial problem for product-mix selection involving 8 decision variables and 21 constraints with fuzzy coefficients is considered as case study. ENORA-II has been evaluated with the existing methodologies in the field and results have been compared with the well-known multi-objective evolutionary algorithm NSGA-II.