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This paper shows, how a genetic algorithm (GA) can be used to model an economic process: the interaction of profit-maximizing oil-exploration firms that compete with each other for a limited amount of oil.
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"[This book] is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem...
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The m-machine, n-job, permutation flowshop problem with the total tardiness objective is a common scheduling problem …
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Traditional time series forecasting models are difficult to capture the nonlinear patterns. Support vector regression (SVR) has been successfully used to solve nonlinear regression and times series problems. However, parameters determination for a SVR model is competent to the forecasting...
Persistent link: https://www.econbiz.de/10014049169
The paper makes an attempt to minimize the makespan and total tardiness in the flow shop scheduling using Artificial Neural Network (ANN). A feed forward back propagation neural network is implemented for the optimal solution of the problem. The network has been trained with the optimal...
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