A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The he...

An intelligent hybrid approach has been developed to integrate various stages in total design, including formulation of productdesign specifications,conceptualdesign, detail design, and manufacture.The integration is achieved by blending multiple artificial intelligence (AI) techniquesand CAD/CAE/CAM into a single environment. It has been applied into power transmissionsystem design. In additio...

Auctions are an important class of mechanisms for resolving multi-agent allocation problems. A genetic algorithm (GA) can be used to design auction mechanisms in order to automatically generate a desired market mechanism in an agent based E-market. One study found a new hybrid market mechanism never be found in the real-world which has very desirable market dynamics according to a measure based...

Simulation and prediction of CO2 laser cutting of Perspex glass has been done by feed forward back propagation Artificial Neural Network (ANN). Experimental data of Taguchi orthogonal array L9 was used to train the ANN model. The simulation results were evaluated and verified with the experiment. In some cases, the prediction errors of Taguchi ANN model was larger than 10% even with Levenberg M...

Single-period problem (SPP) is a classical stochastic inventory model that has become very popular recently. In this research, we developed a SPP with fuzzy environment. The demand of each product is considered as LR-fuzzy variables (ranking fuzzy numbers based on the left and right deviation degrees), and multiple constraints (including service level, batch order, budget, space and upper limit...

An optimization method based on a genetic algorithm (GA) and a boundary element method is applied to solve an electrical impedance tomography problem. The scheme is applied to reconstruct highly irregular shapes and to image and count objects inside a host medium of different impedance. A Pareto multiobjective optimization method is applied to improve the performance of the GA. Comparisons betw...

In this paper, combination between a Fuzzy ARTMAP-based artificial neural network (ANN) model and the genetic algorithm (GA) for performing cooperative learning is described. In our previous work, we have proposed a hybrid network integrating the Fuzzy ARTMAP (FAM) network with the Dynamic Decay Adjustment (DDA) algorithm (known as FAMDDA) for tackling pattern classification tasks. In this work...

0957-4174/$ see front matter 2008 Published by doi:10.1016/j.eswa.2008.10.013 * Corresponding author. E-mail address: [email protected] (K.C. Tan). Real life data sets are often interspersed with noise, making the subsequent data mining process difficult. The task of the classifier could be simplified by eliminating attributes that are deemed to be redundant for classification, as the retenti...

This paper describes the use of a genetic algorithm (GA) to find optimal parameter-values for trading agents that operate in virtual online auction ‘e-marketplaces’, where the rules of those marketplaces are also under simultaneous control of the GA. The aim is to use the GA to automatically design new mechanisms for agent-based e-marketplaces that are more efficient than online markets designe...