Minimizing Makespan for Single Batch Processing Machine with Non-identical Job Sizes Using a Novel Algorithm: Free Search

Zhang, Ya-ling; Chen, Huaping; Shao, Hao; Xu, Rui

doi:10.1109/itcs.2009.43

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Although achievements are preliminary, FS has showed prominent optimization potential. During the process, it is discovered that just like other evolutionary algorithms, FS also has divergence problems, premature convergence problems and so on (Zhang et al, 2009;Zhou et al, 2007;Zhu et al, 2009). The algorithm has no restriction of the probability to zero for the parts of the search space, with which it can cope with heterogeneous optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Application of Takagi–Sugeno fuzzy model optimized with an improved Free Search algorithm to industrial polypropylene melt index prediction

Wang

Hongmei

Zhang

et al. 2016

Transactions of the Institute of Measurement and Control

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A new algorithm is presented for learning the Takagi-Sugeno (T-S) fuzzy model from data by improved Free Search algorithm (IFS), where the rule structure (selection of rules and number of rules), input structure (selection of inputs and number of inputs) and parameters of the T-S fuzzy model are all represented as individuals of the IFS and evolved together such that the optimization of the rule structure, the input structure and the parameters can be achieved simultaneously. The developed IFS-T-S model is used for the prediction of melt index in an industrial propylene polymerization process and the results show that the proposed IFS-T-S model has a good fitting and prediction ability.

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Section: Introductionmentioning

confidence: 99%