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2018 | OriginalPaper | Buchkapitel

A New Method of Dish Innovation Based on User Preference Multi-objective Optimization Genetic Algorithm

verfasst von : Zijie Mei, Yinghua Zhou

Erschienen in: Geo-Spatial Knowledge and Intelligence

Verlag: Springer Singapore

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Abstract

With the improvement of living level, people put forward new requirements for the diversification of diet and greater demand for new dishes. However, it is hard to make food collocation to meet specific requirement, since there are too many foodstuffs, while their nutrition ingredients and incompatibility are not well known to the ordinary people. To solve this problem, food collocation and dish creation to meet the user’s requirement or preference are studied in the paper. First, the data of food composition are collected, the different food guides are referenced and the food component incompatibility is studied. Second, a food nutrition evaluation model is constructed and an improved non-dominated sorting genetic algorithm is proposed. A probability operator is introduced, by analyzing the existing recipes, to control the number of foodstuffs of a dish. A strategy to model user preference is also proposed and the non-dominated solutions are filtered by using the preference model. Third, the experiments are carried out and the experiment results show that the proposed algorithm and nutrition evaluation model can meet the requirements of user preferred dish creation and multi-objective optimization, and has better convergence speed than the original algorithm.

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Literatur
1.
Zurück zum Zitat Pugsee, P., Niyomvanich, M.: Suggestion analysis for food recipe improvement. In: International Conference on Advanced Informatics: Concepts, Theory and Applications, 1–5. IEEE (2015) Pugsee, P., Niyomvanich, M.: Suggestion analysis for food recipe improvement. In: International Conference on Advanced Informatics: Concepts, Theory and Applications, 1–5. IEEE (2015)
2.
Zurück zum Zitat Kular, D.K., Menezes, R., Ribeiro, E.: Using network analysis to understand the relation between cuisine and culture. In: IEEE Network Science Workshop, pp. 38–45. IEEE Computer Society (2011) Kular, D.K., Menezes, R., Ribeiro, E.: Using network analysis to understand the relation between cuisine and culture. In: IEEE Network Science Workshop, pp. 38–45. IEEE Computer Society (2011)
3.
Zurück zum Zitat Pugsee, P., Niyomvanich, M.: Comment analysis for food recipe preferences. In: International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, pp. 1–4. IEEE (2015) Pugsee, P., Niyomvanich, M.: Comment analysis for food recipe preferences. In: International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, pp. 1–4. IEEE (2015)
4.
Zurück zum Zitat Gagliardi, I., Artese, M.T.: Create your menu discovering traditional recipes. In: Digital Heritage, pp. 195–196. IEEE (2016) Gagliardi, I., Artese, M.T.: Create your menu discovering traditional recipes. In: Digital Heritage, pp. 195–196. IEEE (2016)
5.
Zurück zum Zitat Mao, X., Yuan, S., Xu, W., et al.: Recipe recommendation considering the flavor of regional cuisines. In: International Conference on Progress in Informatics and Computing, pp. 32–36. IEEE (2017) Mao, X., Yuan, S., Xu, W., et al.: Recipe recommendation considering the flavor of regional cuisines. In: International Conference on Progress in Informatics and Computing, pp. 32–36. IEEE (2017)
6.
Zurück zum Zitat Singh, H.K., Isaacs, A., Ray, T.: A pareto corner search evolutionary algorithm and dimensionality reduction in many-objective optimization problems. IEEE Trans. Evol. Comput. 15(4), 539–556 (2011)CrossRef Singh, H.K., Isaacs, A., Ray, T.: A pareto corner search evolutionary algorithm and dimensionality reduction in many-objective optimization problems. IEEE Trans. Evol. Comput. 15(4), 539–556 (2011)CrossRef
7.
Zurück zum Zitat Chira, C., Bazzan, A.L.C.: Route assignment using multi-objective evolutionary search. In: IEEE International Conference on Intelligent Computer Communication and Processing, pp. 141–148. IEEE (2015) Chira, C., Bazzan, A.L.C.: Route assignment using multi-objective evolutionary search. In: IEEE International Conference on Intelligent Computer Communication and Processing, pp. 141–148. IEEE (2015)
8.
Zurück zum Zitat Raschip, M., Croitoru, C., Stoffel, K.: Using association rules to guide evolutionary search in solving constraint satisfaction. In: Evolutionary Computation, pp. 744–750. IEEE (2015) Raschip, M., Croitoru, C., Stoffel, K.: Using association rules to guide evolutionary search in solving constraint satisfaction. In: Evolutionary Computation, pp. 744–750. IEEE (2015)
9.
Zurück zum Zitat Li, M., Yang, S., Liu, X.: Diversity comparison of Pareto front approximations in many-objective optimization. IEEE Trans. Cybern. 44(12), 2568 (2014)CrossRef Li, M., Yang, S., Liu, X.: Diversity comparison of Pareto front approximations in many-objective optimization. IEEE Trans. Cybern. 44(12), 2568 (2014)CrossRef
10.
Zurück zum Zitat He, Z., Yen, G.G.: An improved visualization approach in many-objective optimization. In: Evolutionary Computation, pp. 1618–1625. IEEE (2016) He, Z., Yen, G.G.: An improved visualization approach in many-objective optimization. In: Evolutionary Computation, pp. 1618–1625. IEEE (2016)
11.
Zurück zum Zitat Guo, X., Wang, Y., Wang, X.: Using objective clustering for solving many-objective optimization problems. Math. Prob. Eng. 2013(1), 133–174 (2013)MathSciNetMATH Guo, X., Wang, Y., Wang, X.: Using objective clustering for solving many-objective optimization problems. Math. Prob. Eng. 2013(1), 133–174 (2013)MathSciNetMATH
12.
Zurück zum Zitat Maitre, J., Gaboury, S., Bouchard, B., et al.: A new computational method for stator faults recognition in induction machines based on hyper-volumes. In: IEEE International Conference on Electro/Information Technology, pp. 216–220. IEEE (2015) Maitre, J., Gaboury, S., Bouchard, B., et al.: A new computational method for stator faults recognition in induction machines based on hyper-volumes. In: IEEE International Conference on Electro/Information Technology, pp. 216–220. IEEE (2015)
13.
Zurück zum Zitat Chen, X.H., Li, X., Wang, N.: Objective reduction with sparse feature selection for many objective optimization problems. Acta Electronica Sinica 43(7), 1300–1307 (2015) Chen, X.H., Li, X., Wang, N.: Objective reduction with sparse feature selection for many objective optimization problems. Acta Electronica Sinica 43(7), 1300–1307 (2015)
14.
Zurück zum Zitat Hamdan, M.M.: Revisiting the distribution index in simulated binary crossover operator for evolutionary multi objective optimization algorithms. In: Fourth International Conference on Digital Information and Communication Technology and its Applications, pp. 37–41. IEEE (2014) Hamdan, M.M.: Revisiting the distribution index in simulated binary crossover operator for evolutionary multi objective optimization algorithms. In: Fourth International Conference on Digital Information and Communication Technology and its Applications, pp. 37–41. IEEE (2014)
15.
Zurück zum Zitat Yang, D.D., Jiao, L.C., Gong, M.G., et al.: Clone selection algorithm to solve preference multi-objective optimization. J. Softw. 21(1), 1–6 (2010)MathSciNetCrossRef Yang, D.D., Jiao, L.C., Gong, M.G., et al.: Clone selection algorithm to solve preference multi-objective optimization. J. Softw. 21(1), 1–6 (2010)MathSciNetCrossRef
16.
Zurück zum Zitat Vachhani, V.L., Dabhi, V.K., Prajapati, H.B.: Improving NSGA-II for solving multi objective function optimization problems. In: International Conference on Computer Communication and Informatics, pp. 1–6. IEEE (2016) Vachhani, V.L., Dabhi, V.K., Prajapati, H.B.: Improving NSGA-II for solving multi objective function optimization problems. In: International Conference on Computer Communication and Informatics, pp. 1–6. IEEE (2016)
17.
Zurück zum Zitat Güngör, C., Baltacı, F., Erdem, A., et al.: Turkish cuisine: a benchmark dataset with Turkish meals for food recognition. In: Signal Processing and Communications Applications Conference, pp. 1–4. IEEE (2017) Güngör, C., Baltacı, F., Erdem, A., et al.: Turkish cuisine: a benchmark dataset with Turkish meals for food recognition. In: Signal Processing and Communications Applications Conference, pp. 1–4. IEEE (2017)
18.
Zurück zum Zitat Chen, J., Ngo, C.-W: Deep-based ingredient recognition for cooking recipe retrival. ACM Multimed. (2016) Chen, J., Ngo, C.-W: Deep-based ingredient recognition for cooking recipe retrival. ACM Multimed. (2016)
19.
Zurück zum Zitat Chen, J., Ngo, C.W.: Deep-based ingredient recognition for cooking recipe retrieval. In: ACM on Multimedia Conference, pp. 32–41. ACM (2016) Chen, J., Ngo, C.W.: Deep-based ingredient recognition for cooking recipe retrieval. In: ACM on Multimedia Conference, pp. 32–41. ACM (2016)
20.
Zurück zum Zitat Yao, Y.: Chinese Dietary Reference Intake. DRIs. Acta Nutrimenta Sinica 36(04), 308 (2014). (in Chinese) Yao, Y.: Chinese Dietary Reference Intake. DRIs. Acta Nutrimenta Sinica 36(04), 308 (2014). (in Chinese)
Metadaten
Titel
A New Method of Dish Innovation Based on User Preference Multi-objective Optimization Genetic Algorithm
verfasst von
Zijie Mei
Yinghua Zhou
Copyright-Jahr
2018
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-13-0896-3_32