The huge demand for real time services in wireless mesh networks (WMN) creates many challenging issues for providing quality of service (QoS). Designing of QoS routing protocols, which optimize the multiple objectives is computationally intractable. This paper proposes a new model for routing in WMN by using Modified Non-dominated Sorting Genetic Algorithm-II (MNSGA-II). The objectives which ar...

The aim of this paper is to propose a simple but powerful multiobjective hybrid genetic algorithm and to examine its search ability through computational experiments on commonly used test problems in the literature. We first propose a new multiobjective hybrid genetic algorithm, which is designed by combining local search with an EMO (evolutionary multiobjective optimization) algorithm. In the ...

Handling uncertainties for parameters in nonlinear constraints using chance constrained programming (CCP) is not as straight forward as its linear counterparts. A simulation based CCP approach which can be thought as an alternative to handle such a situation, has been adopted in this work while solving a multi-objective optimization problem of an industrial grinding operation under various para...

controller design and optimization problems, with more than one objective, are referred as multiple objectives or multiple attributed problems. in this paper, a novel method is proposed for designing optimum pid controller that is called genetic multiple attributed decision making method (gmadm). this method is newer than the previous methods and in this paper some options are considered that h...

Abstract Optimally designed water distribution networks (WDNs) make engineers’ tasks difficult due to various challenges like non-linearity between head-loss and flow, commercially available distinct diameters, combinatorial, nondeterministic polynomial-time hard problems a large number of decision variables. This paper develops new hybrid NSGA-II algorithm augmented with random multi-point cro...

Atmospheric pollutants mainly produced by thermal power plants compel to utilize green energy sources such as renewable and hydroelectric in a system. But due blinking behavior of very high rate outages, it has detrimental consequence on overall grid. Demand side management (DSM) programs decrease cost improve system security. This study proposes non-dominated sorting genetic algorithm-II (NSGA...

[1] A methodology extending the Cross Entropy combinatorial optimization method originating from an adaptive algorithm for rare events simulation estimation, to multiobjective optimization of water distribution systems design is developed and demonstrated. The single objective optimal design problem of a water distribution system is commonly to find the water distribution system component chara...

In this paper, we propose a method of MultiObjective Genetic Algorithms (MOGAs), NSGA-II and SPEA2, for document clustering with semantic similarity measures based on WordNet. The MOGAs showed a high performance compared to other clustering algorithms. The main problem in the application of MOGAs for document clustering in the Vector Space Model (VSM) is that it ignores relationships between im...

Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate di...

Lens system design provides ideal problems for evolutionary algorithms: a complex nonlinear optimization task, often with intricate physical constraints, for which there is no analytical solutions. This paper demonstrates, through the use of two evolution strategies, namely non-isotropic SA-ES and CMA-ES, as well as multiobjective NSGA-II optimization, the human competitiveness of an approach w...