Timothy Ganesan

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A fairly reasonable result was obtained for nonlinear engineering problems using the optimization techniques such as neural network, genetic algorithms, and fuzzy logic independently in the past. Increasingly, hybrid techniques are being used to solve the nonlinear problems to obtain a better output. This paper discusses the use of neuro-genetic hybrid(More)
In multi-objective engineering optimization, it is very rare that there exists a unique ideal solution that covers every aspect of the problem. Thus, it is very useful for the decision maker to have multiple options prior to the selection of the best solution. In this work, a novel evolutionary normal boundary intersection (ENBI) method is introduced to(More)
The global energy sector faces major challenges in providing sufficient energy to the worlds ever-increasing energy demand. Options to produce greener, cost effective, and reliable source of alternative energy need to be explored and exploited. One of the major advances in the development of this sort of power source was done by integrating (or hybridizing)(More)
One of the major advances in recent years is the integration of multiple alternative energy sources, e.g., wind turbine generators, photovoltaic cell panels and fuel-fired generators, equipped with storage batteries to form a distributed generation (DG) power system. Nevertheless, cost effectiveness, reliability and pollutant emissions are still major(More)
Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as(More)