In this paper we propose two novel approaches for solving constrained multi-objective optimization problems using steady state GAs. These methods are intended for solving real-world application problems that have many constraints and very small feasible regions. One method called Objective Exchange Genetic Algorithm for Design Optimization (OEGADO) runs several GAs concurrently with each GA opt...

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...

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...

The competitive market and declined economy have increased the relevant importance of making supply chain network efficient. This has created many motivations to reduce the cost of services, and simultaneously, to increase the quality of them. The network as a tri-echelon one consists of Suppliers, Warehouses or Distribution Centers (DCs), and Retailer nodes. To bring the problem closer to real...

Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(mN3) computational complexity (where m is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algo...

Abstract. Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algor...

Many studies are performed by researchers about Shell and Tube Heat Exchanger but the Multi-Objective Big Bang-Big Crunch algorithm (MOBBA) technique has never been used in such studies. This paper presents application of Thermal-Economic Multi-Objective Optimization of Shell and Tube Heat Exchanger Using MOBBA. For optimal design of a shell and tube heat exchanger, it was first thermally model...

In this paper an accurate method is presented for determining of the device sizes in a RF circuit based on genetic algorithm (GA). HSPICE RF simulation is used for evaluating of the fitness of the circuit specifications per every iteration of the GA. Also an example for a LNA is presented for evaluating of non-dominated sorting genetic algorithm (NSGA-II) as a method of multi objective genetic ...

with the huge global and wide range of attention placed upon quality, promoting and optimize the reliability of the products during the design process has turned out to be a high priority. in this study, the researcher have adopted one of the existing models in the reliability science and propose a bi-objective model for redundancy allocation in the series-parallel systems in accordance with th...

In Wireless Sensor Network (WSN), coverage and connectivity are the vital challenges in target-based region. The linear objective is to find positions cover complete target nodes between each sensor for data forwarding towards base station given a grid with points potential placement position. this paper, multiobjective problem on WSN (t-WSN) derived, which minimizes number of deployed n...