a novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (wds) for the purpose of its hydraulic model calibration is presented. the problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. the objectives are to maximise the calibrated model accuracy and to minimise the number of sampling d...

In allusion to remove Racian noise while lessen the loss of details as low as possible, this paper proposed an filter algorithm which comprehensive utilize Multi-Objective Genetic Algorithm (MOGA) and Shearlet transform based on a Multi-scale Geometric Analysis (MGA) theory. First, it performs a wavelet multi-scale decomposition of image. Then, it builds target function in MOGA by several evalu...

The multiobjective genetic algorithm (MOGA) has been applied to various real-world problems in a variety of fields, most prominently in control systems engineering, with considerable success. However, a recent empirical analysis of multiobjective evolutionary algorithms (MOEAs) has suggested that a MOGA-based algorithm performed poorly across a diverse set of two-objective test problems. In thi...

PurposeThe purpose of this paper is to present a hierarchical circuit synthesis system with a Hybrid DLO-MOGA (Deterministic Local Optimization Multi-Objective Genetic Algorithm) optimization scheme for system level synthesis. Design/methodology/approachThe use of a local optimization with a deterministic algorithm based on linear equations which is computationally efficient and improves the fe...

This paper presents the nonlinear time series prediction using Lyapunov theory-based fuzzy neural network and multi-objective genetic algorithm (MOGA). The architecture employs fuzzy neural network (FNN) structure and the tuning of the parameters of FNN using the combination of the MOGA and the modified Lyapunov theory-based adaptive filtering algorithm (LAF). The proposed scheme has been used ...

Multi-label spatial classification based on association rules with multi objective genetic algorithms (MOGA) enriched by semi supervised learning is proposed in this paper. It is to deal with multiple class labels problem. In this paper we adapt problem transformation for the multi label classification. We use hybrid evolutionary algorithm for the optimization in the generation of spatial assoc...

In this article, our interest is focused on the automatic learning of Boolean queries in information retrieval systems (IRSs) by means of multi-objective evolutionary algorithms considering the classic performance criteria, precision and recall. We present a comparative study of four well-known, general-purpose, multi-objective evolutionary algorithms to learn Boolean queries in IRSs. These evo...

This paper presents an automatic optimization method for compliant constant force mechanisms, which eliminates the need time-consuming parameter tuning and complex model design in conventional process. The proposed framework is based on finite-element analysis (FEA) multi-objective genetic algorithm (MOGA) methods designed two steps: First, preliminary mechanism carried out to roughly encompass...

The paper describes a rank-based fitness assignment method for Multiple Objective Genetic Algorithms (MOGAs). Conventional niche formation methods are extended to this class of multimodal problems and theory for setting the niche size is presented. The fitness assignment method is then modified to allow direct intervention of an external decision maker (DM). Finally, the MOGA is generalised fur...

This paper considers a flowshop scheduling problem of a manufacturing cell that contains families of jobs whose setup times are dependent on the manufacturing ............ sequence of the families. Two objectives, namely the makespan and total flow time, have been considered simultaneously in this work. Since minimization of each of these two objectives is an NpHard problem, a Multi-Objective G...