Multi-objective IIR Filter Design using Nondominated Sorting Genetic Algorithm-II
نویسندگان
چکیده
منابع مشابه
Optimal Placement and Sizing of Distributed Generation Via an Improved Nondominated Sorting Genetic Algorithm II
The use of distributed generation units in distribution networks has attracted the attention of network managers due to its great benefits. In this research, the location and determination of the capacity of distributed generation (DG) units for different purposes has been studied simultaneously. The multi-objective functions in the optimization model are reducing system line losses; reducing v...
متن کاملIsothermal Reactor Network Synthesis Using Coupled NonDominated Sorting Genetic Algorithm-II (NSGAII) with Quasi Linear Programming (LP) Method
In this study a new and robust procedure is presented to solve synthesis of isothermal reactor networks (RNs) which considers more than one objective function. This <span style="font-size: 9pt; color: #0...
متن کاملMulti-objective Traffic Signal Timing Optimization Using Non-dominated Sorting Genetic Algorithm II
This paper presents the application of Nondominated Sorting Genetic Algorithm II (NSGA II) in solving multiple-objective signal timing optimization problem (MOSTOP). Some recent researches on intersection signal timing design optimization and multi-objective evolutionary algorithms are summarized. NSGA II, which can find more of the Pareto Frontiers and maintain the diversity of the population,...
متن کاملSolving a New Multi-objective Inventory-Routing Problem by a Non-dominated Sorting Genetic Algorithm
This paper considers a multi-period, multi-product inventory-routing problem in a two-level supply chain consisting of a distributor and a set of customers. This problem is modeled with the aim of minimizing bi-objectives, namely the total system cost (including startup, distribution and maintenance costs) and risk-based transportation. Products are delivered to customers by some heterogeneous ...
متن کاملOptimal Thermodynamic Design of Turbofan Engines using Multi-objective Genetic Algorithm
The aim of this study is to optimize performance functions of turbofan engines considering the off-design model of turbofan engine as well as employing multi-objective genetic algorithm. The design variables including high-pressure compressor pressure ratio, low-pressure compressor pressure ratio, fan pressure ratio and bypass ratio are calculated in such a way that the corresponding functions ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Indian Journal of Science and Technology
سال: 2016
ISSN: 0974-6846,0974-5645
DOI: 10.17485/ijst/2016/v9i47/102764