The NBI-NLPQLP optimization method is tested on several multi-objective optimization problems. Its performance is compared to that of MOGA-II: since NBI-NLPQLP is based on the classical gradientbased NLPQLP, it is fast and accurate, but not as robust, in comparison with the genetic algorithm. Furthermore a discontinuous Pareto frontier can give rise to problems in the NBI’s convergence. In orde...

A strategy by multi-objective genetic algorithm (MOGA) combined with Kriging response surface is proposed for optimum design of wavy fin tube in an air cooler, while minimum pressure loss factor, maximum heat transfer factor and overall performance as three objective functions. The results show that the effects height density on are positive wave number angle negative; parallel higher than stag...

Renovation is known to be a complicated type of construction project and prone errors compared new constructions. The need carry out renovation work while keeping normal business activities running, coupled with strict governmental building regulations, presents an important challenge affecting performance. Given the current availability robust hardware software, information modeling (BIM) opti...

MOTIVATION With an increase in the number of known biological functions of non-coding RNAs, the importance of RNA sequence alignment has risen. RNA sequence alignment problem has been investigated by many researchers as a mono-objective optimization problem where contributions from sequence similarity and secondary structure are taken into account through a single objective function. Since ther...

Decision making in engineering design can be effectively addressed by using genetic algorithms to solve multi-objective problems. These multi-objective genetic algorithms (MOGAs) are well suited to implementation in a Service Oriented Architecture. Often the evaluation process of the MOGA is compute-intensive due to the use of a complex computer model to represent the real-world system. The eme...

Title of Dissertation: ROBUST OPTIMIZATION AND SENSITIVITY ANALYSIS WITH MULTI-OBJECTIVE GENETIC ALGORITHMS: SINGLEAND MULTIDISCIPLINARY APPLICATIONS Mian Li, Doctor of Philosophy, 2007 Dissertation directed by: Shapour Azarm, Professor Department of Mechanical Engineering Uncertainty is inevitable in engineering design optimization and can significantly degrade the performance of an optimized ...

Emerging network applications require the delivery of packets from one or more senders to a group of receivers. For this reason QoS Multicast Routing Algorithm is a key problem for the researchers. This paper shows a QoS Multicast Genetic Algorithm (GA) that is applied to a multi-layer wireless system composed of a GEO DVB-RCS Satellite and a set of High Altitude Platforms (HAPs). This architec...

Two techniques are combined during the design of an optimal controller: Linear Matrix Inequalities (LMIs) and Multi-objective Genetic Algorithms (MOGAs). In this paper the LMI optimization technique is used to obtain a single controller while MOGA is used to convert the controller design into a multi-objective optimization procedure. The combination of these techniques is proposed in this docum...