TSK-type recurrent fuzzy network design by the hybrid of genetic algorithm and particle swarm optimization

Juang, Chia‐Feng; Liou, Yuan-Chang

doi:10.1109/icsmc.2004.1400674

Cited by 9 publications

References 6 publications

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Determining consignment inventory strategy for a vendor and multiple buyers using a hybrid metaheuristic algorithm

Molamohamadi

Sharifyazdi

Arshizadeh

et al. 2013

Production & Manufacturing Research

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This paper considers a centralized supply chain with consignment inventory (CI) system, where a vendor keeps a finished product and supplies it at the same price to multiple buyers. CI is a process where the buyer pays with delay for the goods supplied by the vendor. Considering the time value of money, this study compares two types of delay in payment in CI, which have been rarely considered (real use and order to order). Furthermore, two different metaheuristic algorithms, genetic algorithm (GA) and a hybrid algorithm, containing GA and particle swarm optimization algorithm, are used to maximize the supply chain net profit and calculate the proper values. Finally, a sensitivity analysis is performed to examine the effects of each parameter on the total net profit. Moreover, by applying a paired t-test, a comparison is made between two types of CI system and also between GA and the hybrid algorithm.

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Determining consignment inventory strategy for a vendor and multiple buyers using a hybrid metaheuristic algorithm

Molamohamadi

Sharifyazdi

Arshizadeh

et al. 2013

Production & Manufacturing Research

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Design of Optimal Orbit and Constant Force for Soft-Landing of Lunar Lander

Liu

Duan

2006

2006 Chinese Control Conference

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This paper deals with the soft landing of lunar lander. A parametric piece-wise constant controller is developed, which arbitrarily approaches the optimal continuous controller and has the parameters whose number is equal to the rank of the system. This controller transforms the optimal control to the parameter optimization which is easily solved by the standard mathematic programming. The soft landing problem is treated by using this controller. Optimal parameters are derived by the genetic algorithm. At last, the simulation results illustrate the feasibility and advantage of our approach.

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Novel Adaptive Hybrid Optimization (AHO) Technique Using Biologically-Inspired Algorithms with FLC

Soliman

Tan

Abdullah

2008

2008 International Conference on Computer Science and Software Engineering

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TSK-type recurrent fuzzy network design by the hybrid of genetic algorithm and particle swarm optimization

Cited by 9 publications

References 6 publications

Determining consignment inventory strategy for a vendor and multiple buyers using a hybrid metaheuristic algorithm

Determining consignment inventory strategy for a vendor and multiple buyers using a hybrid metaheuristic algorithm

Design of Optimal Orbit and Constant Force for Soft-Landing of Lunar Lander

Novel Adaptive Hybrid Optimization (AHO) Technique Using Biologically-Inspired Algorithms with FLC

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