The non-dominated sorting genetic algorithm II (NSGA-II) is the most intensively used multi-objective evolutionary (MOEA) in real-world applications. However, contrast to several simple MOEAs analyzed also via mathematical means, no such study exists for NSGA-II so far. In this work, we show that runtime analyses are feasible NSGA-II. As particular results, prove with a population size larger t...

Abstract Robot manipulators perform a point-point task under kinematic and dynamic constraints. Due to multi-degree-of-freedom coupling characteristics, it is difficult find better desired trajectory. In this paper, multi-objective trajectory planning approach based on an improved elitist non-dominated sorting genetic algorithm (INSGA-II) proposed. Trajectory function planned with new composite...

Penjadwalan operasi pasien merupakan aktifitas penting pada kegiatan operasional rumah sakit, karena menentukan waktu pasien-pasien tertangani dengan baik. Permasalahan ini dimodelkan sebagai masalah optimasi multi-obyektif yaitu meminimalkan yang digunakan saat tindakan operasi. Masalah penjadwalan dirumuskan mixed integer programming (MIP), sehingga variabel merepresentasikan jadwal kasus lay...

A key concern in artificial-life-oriented research in complex systems has been the relationship between the dynamical behaviour of cellular automata (CA) and their computational ability. Along this line, evolutionary methods have been used to look for CA with predefined computational behaviours, the most widely studied task having been the Density Classification Task (DCT). It has recently been...

In this paper, a control technique based on simultaneous regulation of all control coefficients for Unified Power Flow Controller (UPFC) and Power System Stabilizer (PSS) is proposed. Non-Dominated Sorting Particle Swarm Optimization (NSPSO) has been used for parameter optimization. Studies in time and frequency domains for single machine infinite bus power system (SMIB) in different operationa...

A method for computing minimum cost trajectory planning for industrial robot manipulators is presented. The objective function minimizes the cost function with the constraints being joint positions, velocities, jerks and torques by considering dynamic equations of motion. A clamped cubic spline is used to represent the trajectory. This is a non-linear constrained optimization problem. The probl...

We present a multiobjective genetic algorithm that incorporates various genetic algorithm techniques that have been proven to be efficient and robust in their problem domain. More specifically, we integrate rank based selection, adaptive niching through coevolutionary sharing, elitist recombination, and non-dominated sorting into a multiobjective genetic algorithm called ERMOCS. As a proof of c...

In this paper, a simple but efficient Non-dominated Sorting Genetic Algorithm (NSGA) II based technique is proposed for optimizing the Degree of Hybridization (DOH) in parallel passenger hybrid cars. The authors’ objective is to improve performance, maximize fuel economy and at the same time, minimize mass and emissions as much as possible, by optimal selection of DOH. The NSGA-II, which is a m...

 Sorting is the process of arranging the data into a meaningful order so that we can analyze it more effectively. Sorting is a key requirement in many applications like digital signal processing, scientific computing, network processing etc. This paper presents an area efficient technique for designing high throughput and low latency sorting units. Two popular parallel sorting algorithms are u...

This research project focuses on modelling the large-scale morphodynamics of low-slope rivers dominated by mixed sediment, such as the Dutch part of the Rhine River. Usually we simply neglect the effects of sorting and variability in dune dimensions on the large-scale morphodynamics. This paper shows that these effects are not negligible.