Electro-thermal co-design of power modules is required to maximize the capabilities promising semiconductor devices. The chip layout on substrate, which restricted by size module determines electrical and thermal characteristics module. This paper proposes a optimization strategy for based multiobjective electro-thermal design algorithm. parasitic inductance resistance SiC are evaluated using u...

In this paper, a fractional order (FO) PID controller is designed to take care of various contradictory objective functions for an Automatic Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for greater effectiveness, is used for the multi-objective optimization problem. The Pareto fronts showing ...

In this study, our aim is to predict the compositions of zinc electroplating bath using machine learning method and optimize organic additives with NSGA-II (Non-dominated Sorting Genetic Algorithm) optimization algorithm. Mask RCNN was utilized classify coated plates according their appearance. The names classes were defined as ”Full Bright”, Fail”, ”HCD Fail” ”LCD Fail”. intersection over unio...

—In this paper, we present a modeling and simulation framework for conducting the adequacy assessment of a wind-integrated power system accounting for the associated uncertainties. A multi-perceptron artificial neural network (NN) is trained by a non-dominated sorting genetic algorithm–II (NSGA-II) to forecast point-values and prediction intervals (PIs) of the wind power and load. The output of...

This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The cas...

Semi-active fluid viscous dampers as a subset of control systems have shown their ability to reduce seismic responses of tall buildings. In this paper, multi-objective optimization of the performance of this group of dampers in reducing the seismic responses of buildings is studied using multi-objective genetic algorithms. For numerical example, two 7 and 18 stories buildings are chosen and mod...

In this paper, a novel mathematical model for a preemption multi-mode multi-objective resource-constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. Although optimization of bi-objective problems with due dates is an essential feature of real projects, little effort has been made in studying the P-MMRCPSP while due dates are included i...

the aim of a multi-mode resource-constrained project scheduling problem (mrcpsp) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). these goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategi...

Abstract The flexible job-shop scheduling problem (FJSP) is a critical model in manufacturing systems that assigns operations from different jobs to various machines. However, optimizing multiple targets during the production process always necessary. While non-dominated sorting genetic algorithm (NSGA-II) an effective method solve multi-objective FJSP, it can have main drawbacks of converging ...

Determining the contribution of an agent to a system-level objective function (credit assignment) is a key area of research in cooperative multiagent systems. Multi-objective optimization is a growing area of research, though mostly focused on single agent settings. Many real-world problems are multiagent and multi-objective, (e.g., air traffic management, scheduling observations across multipl...