In this paper, a novel approach based on handling constraints as objectives together with a modified Parks & Miller elitist technique, to solve constrained multiobjective optimization problems, is analyzed with Niched Pareto Genetic Algorithm. The performance of this approach is compared with the classical procedure of handling constraints that is the exterior penalty function method. Results a...

In this paper, we propose a calculation method of local dominance and enhance multiobjective evolutionary algorithms by performing a distributed search based on local dominance. We divide the population into several sub-populations by using declination angles of polar coordinate vectors in the objective space. We calculate local dominance for individuals belonging to each sub-population based o...

This paper presents the Parallel Single Front Genetic Algorithm (PSFGA), a parallel Pareto-based algorithm for multiobjective optimization problems based on an evolutionary procedure. In this procedure, a population of solutions is sorted with respect to the values of the objective functions and partitioned into subpopulations which are distributed among the processors. Each processor applies a...

We propose a new technique for the automatic generation of optimal ad-hoc ans\"atze classification by using quantum support vector machine (QSVM). This efficient method is based on NSGA-II multiobjective genetic algorithms which allow both maximize accuracy and minimize ansatz size. It demonstrated validity practical example with non-linear dataset, interpreting resulting circuit its outputs. a...

Abstract In the field of preference-based evolutionary multiobjective optimization, optimization algorithms are required to search for Pareto optimal solutions preferred by decision maker (DM). The reference point is a type techniques that effectively describe preferences DM. So far, either static or interactive with process. However, existing do not cover all application scenarios. A novel cas...

With the enormous breadth of potential bandwidth provided by WDM optical networks, the study of prevention and protection against failures becomes critical. The protection based on pCycles is a novel approach, based on optimal pre-configured cycles of protection to provide speed and efficient recovery. This paper proposes a Multiobjective Optimization approach to solve the problem of selecting ...

This work introduces an approach for taking into account the uncertainty of pipe friction coefficients and nodal demands in the hydraulic analysis of water supply networks. For this purpose, uncertainties are represented by fuzzy numbers and incorporated into the network's governing equations. Input uncertainties are spread out on the network and influence its hydraulic responses, including pip...

in this study, a two-objective mixed-integer linear programming model (milp) for multi-product re-entrant flow shop scheduling problem has been designed. as a result, two objectives are considered. one of them is maximization of the production rate and the other is the minimization of processing time. the system has m stations and can process several products in a moment. the re-entrant flow sho...

This paper presents the Necessary-preference-enhanced Evolutionary Multiobjective Optimizer (NEMO), which combines an evolutionary multiobjective optimization with robust ordinal regression within an interactive procedure. In the course of NEMO, the decision maker is asked to express preferences by simply comparing some pairs of solutions in the current population. The whole set of additive val...

Abstract—In this paper, a hybrid multiobjective evolutionary algorithm, MOEA/D-GO (Multiobjective Evolutionary Algorithm Based on Decomposition combined with Enhanced Genetic Operators), is proposed for fragment-type antenna design. It combines the ability and efficiency of MOEA/D to deal with multiobjective optimization problems with the specific character of two-dimensional chromosome coding ...