Multiobjective fireworks optimization for variable-rate fertilization in oil crop production

Applied Soft Computing Journal

Volumn 13, Issue 11, 2013, Pages 4253-4263

  Zheng, Yu Jun ^a   Song, Qin ^b   Chen, Sheng Yong ^a  

^a ZHEJIANG UNIVERSITY OF TECHNOLOGY   (China)

^b BEIJING UNIVERSITY OF AGRICULTURE   (China)

Author keywords

Differential evolution (DE); Fireworks optimization algorithm (FOA); Hybrid optimization method; Multiobjective optimization; Precision agriculture; Variable rate fertilization (VRF)

Indexed keywords

AGRICULTURE; CROPS; CULTIVATION; ENERGY UTILIZATION; EVOLUTIONARY ALGORITHMS; EXPLOSIVES; MULTIOBJECTIVE OPTIMIZATION; PARETO PRINCIPLE;

DIFFERENTIAL EVOLUTION; HYBRID OPTIMIZATION METHOD; OPTIMIZATION ALGORITHMS; PRECISION AGRICULTURE; VARIABLE RATE FERTILIZATION;

OPTIMIZATION;

EID: 84885388383     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2013.07.004     Document Type: Article

References (57)

1. K.S. Raju, D.N. Kumar, Multicriterion decision making in irrigation planning, Agricultural Systems 62 (1999) 117-129. (Pubitemid 30059368)
2. S.Y. Chen, J.Q. Ma, L. Qiu, Fuzzy optimization of multi-dimensional multiobjective dynamic programming and its application to farm irrigation, Journal of Hydraulic Engineering 33 (2002) 33-38.
3. M. Kilic, S. Anac, Multi-objective planning model for large scale irrigation systems: method and application, Water Resources Management 24 (2010) 3173-3194.
4. Y.J. Wang, D.K. Zhang, The optimization model of multi-objective fertilization of rice seedbed, International Journal of Biomathematics 18 (2003) 467-472.
5. Y. Yuan, M. Li, L. Li, G. Zhang, X. Chen, L. Wang, Algorithm of fertilization model based on intelligent computing, Transactions of the Chinese Society of Agricultural Engineering 24 (2008) 116-119.
6. W. Lan, P. Mao, D. Du, J. Wang, Decision-making method for variable-rate fertilization based on RBF neural network, Journal of Anhui Agricultural Sciences 35 (2007) 6505-6507.
7. H. Yu, J. Liu, D. Jin, Y. Yang, D. Liu, A novel neural network ensemble method and its application in precision fertilization, Journal of Computer Research & Development 47 (2010) 1530-1538.
8. C.A. Coello Coello, G.B. Lamont, D.A. Van Veldhuizen, Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation), Springer-Verlag, New York, 2006.
9. N. Srinivas, K. Deb, Multiobjective optimization using nondominated sorting in genetic algorithms, Evolutionary Computation 2 (1994) 221-248.
10. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multi-objective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation 6 (2002) 182-197. (Pubitemid 34555372)
11. E. Zitzler, L. Thiele, Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach, IEEE Transactions on Evolutionary Computation 3 (1999) 257-271. (Pubitemid 30544879)
12. E. Zitzler, M. Laumanns, L. Thiele, SPEA2: Improving the strength Pareto evolutionary algorithm, in: K. Giannakoglou, D. Tsahalis, J. Periaux, P. Papailou, T. Fogarty (Eds.), Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems, International Center for Numerical Methods in Engineering, 2001, Athens, Greece.
13. J. Knowles, D. Corne, M-PAES: a memetic algorithm for multiobjective optimization, in: Proceedings of 2000 Congress on Evolutionary Computation, Piscataway, IEEE Service Center, vol. 1, 2000, pp. 325-332.
14. H.A. Abbass, R. Sarker, C. Newton, PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems, in: Proceedings of the Congress on Evolutionary Computation, Piscataway, IEEE Service Center, vol. 2, 2001, pp. 971-978. (Pubitemid 32806246)
15. X. Li, A non-dominated sorting particle swarm optimizer for multiobjective optimization, Lecture Notes in Computer Science 2723 (2003) 37-48.
16. Z. Zhang, Immune optimization algorithm for constrained nonlinear multiobjective optimization problems, Applied Soft Computing 7 (2007) 840-857. (Pubitemid 46551921)
17. C.K. Goh, K.C. Tan, D.S. Liu, S.C. Chiam, A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design, European Journal of Operational Research 202 (2010) 42-54.
18. C. Shi, Z. Yan, Z. Shi, L. Zhang, A fast multi-objective evolutionary algorithm based on a tree structure, Applied Soft Computing 10 (2010) 468-480.
19. Y. Cooren, M. Clerc, P. Siarry, MO-TRIBES: an adaptive multiobjective particle swarm optimization algorithm, Computational Optimization and Applications 49 (2011) 379-400.
20. W.K. Mashwani, A. Salhi, A decomposition-based hybrid multiobjective evolutionary algorithm with dynamic resource allocation, Applied Soft Computing 12 (2012) 2765-2780.
21. D.B. Chen, F. Zou, J.T. Wang, A multi-objective endocrine PSO algorithm and application, Applied Soft Computing 11 (2011) 4508-4520.
22. A. Zhou, B.Y. Qu, H. Li, S.Z. Zhao, P.N. Suganthan, Q. Zhang, Multiobjective evolutionary algorithms: a survey of the state of the art, Swarm and Evolutionary Computation 1 (2011) 32-49.
23. S.Y. Chen, Y.J. Zheng, C. Cattani, W.L. Wang, Modeling of biological intelligence for SCM system optimization, Computational and Mathematical Methods in Medicine (2012), doi:10.1155/2012/769702.
24. Y.J. Zheng, S.Y. Chen, Y. Lin, W.L. Wang, Bio-inspired optimization of sustainable energy systems: a review, Mathematical Problems in Engineering 2013 (2013), AID 354523, 12 pages.
25. T. Niknam, M. Zare, J. Aghaei, Scenario-Based multiobjective volt/var control in distribution networks including renewable energy sources, IEEE Transactions on Power Delivery 27 (2012) 2004-2019.
26. P. Ahmadi, M.A. Rosen, I. Dincer, Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm, Energy 46 (2012) 21-31.
27. T. Niknam, H.Z. Meymand, H.D. Mojarrad, An efficient algorithm for multiobjective optimal operation management of distribution network considering fuel cell power plants, Energy 36 (2011) 119-132.
28. T. Niknam, A. Kavousifard, S. Tabatabaei, J. Aghaei, Optimal operation management of fuel cell/wind/photovoltaic power sources connected to distribution networks, Journal of Power Sources 196 (2011) 8881-8896.
29. P. Ahmadi, I. Dincer, Thermodynamic and exergoenvironmental analyses, and multi-objective optimization of a gas turbine power plant, Applied Thermal Engineering 31 (2011) 2529-2540.
30. P. Ahmadi, A. Almasi, M. Shahriyari, I. Dincer, Multi-objective optimization of a combined heat and power (CHP) system for heating purpose in a paper mill using evolutionary algorithm, International Journal of Energy Research 36 (2012) 46-63.
31. S.E. Shakib, S.R. Hosseini, M. Amidpour, C. Aghanajafi, Multi-objective optimization of a cogeneration plant for supplying given amount of power and fresh water, Desalination 286 (2012) 225-234.
32. J.M. Reddy, D.N. Kumar, Evolving strategies for crop planning and operation of irrigation reservoir system using multi-objective differential evolution, Irrigation Science 26 (2008) 177-190. (Pubitemid 350277533)
33. Y. Tan, Y. Zhu, Fireworks algorithm for optimization, Lecture Notes in Computer Science 6145 (2010) 355-364.
34. J. Kennedy, R. Eberhart, Particle swarm optimization, in: Proceedings of IEEE International Conference on Neural Networks, Perth WA, Australia, 1995, pp. 1942-1948.
35. Y. Tan, Z.M. Xiao, Clonal particle swarm optimization and its applications, in: Proceedings of IEEE Congress on Evolutionary Computation, Piscataway, IEEE Service Center, 2007, pp. 2303-2309.
36. Y.J. Zheng, X.L. Xu, H.F. Ling, S.Y. Chen, A hybrid fireworks optimization method with differential evolution operators, Neurocomputing (2013) (in press).
37. R. Storn, K. Price, Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization 11 (1997) 341-369.
38. J.L. Yu, Agricultural Experiments with Polydesign, Beijing University of Agriculture Press, Beijing, 1993.
39. R.K. Ru, Soil & Plant Nutrition Principles and Fertilization, Chemical Industry Press, Beijing, 1998.
40. B.W. Silverman, Density Estimation for Statistics and Data Analysis, Chapman and Hall, London, 1986.
41. Z. Cai, Y. Wang, A multiobjective optimization-based evolutionary algorithm for constrained optimization, IEEE Transactions on Evolutionary Computation 10 (2006) 658-675. (Pubitemid 46445555)
42. M.S. Alam, M.M. Islam, X. Yao, K. Murase, Diversity Guided Evolutionary Programming: a novel approach for continuous optimization, Applied Soft Computing 12 (2012) 1693-1707.
43. J. Hajek, A. Szollos, J. Sistek, A new mechanism for maintaining diversity of Pareto archive in multi-objective optimization, Advances in Engineering Software 41 (2010) 1031-1057.
44. W. Gong, Z. Cai, A multiobjective differential evolution algorithm for constrained optimization, in: Proceedings of IEEE Congress on Evolutionary Computation, Washington, DC, 2008, pp. 181-188.
45. Q.Y. Guo, Z.Y. Li, X.W. Tu, Plant nutritional aspects and effects of fertilizer application in rapeseed in red-yellow soil of south China, Chinese Journal of Oil Crop Sciences 23 (2001) 51-55.
46. Y. Liu, H. Wu, J. Huang, Z. Zhuang, J. Lin, Y. Liu, Preliminary report on fertilization trial of Canarium album, Guangdong Forestry Science and Technology 23 (2007) 13-15.
47. W.Y. Qian, J. Yang, Y. Yang, H.J. Wang, J.X. Wu, A new random group search algorithm for solving the multi-objective programming problems, Journal of Liaoning Normal University 30 (2007) 141-143.
48. E. Zitzler, K. Deb, L. Thiele, Comparison of multiobjective evolutionary algorithms: empirical results, Evolutionary Computation 8 (2000) 173-195.
49. D. Karaboga, B. Basturk, On the performance of artificial bee colony (ABC) algorithm, Applied Soft Computing 8 (2008) 687-697. (Pubitemid 47374599)
50. S. Chaudhuri, K. Deb, An interactive evolutionary multi-objective optimization and decision making procedure, Applied Soft Computing 10 (2010) 496-511.
51. M.D. Madronero, D. Peidro, P. Vasant, Vendor selection problem by using an interactive fuzzy multi-objective approach with modified s-curve membership functions, Computers & Mathematics with Applications 60 (2010) 1038-1048.
52. D. Peidro, P. Vasant, Transportation planning with modified s-curve membership functions using an interactive fuzzy multi-objective approach, Applied Soft Computing 11 (2011) 2656-2663.
53. H.H. Nasaba, A.S. Milanib, An improvement of quantitative strategic planning matrix using multiple criteria decision making and fuzzy numbers, Applied Soft Computing 12 (2012) 2246-2253.
54. T. Niknam, M. Zare, J. Aghaei, R.A. Abarghooee, Interactive multiobjective daily volt/var control of distribution networks considering wind power and fuelcell power plants, Journal of Renewable and Sustainable Energy 4 (2012) 1-26.
55. T. Ganesan, P. Vasant, I. Elamvazuthi, Optimization of nonlinear geological structure mapping using hybrid neuro-genetic techniques, Mathematical and Computer Modelling 54 (2011) 2913-2922.
56. K. Wang, Y.J. Zheng, A new particle swarm optimization algorithm for fuzzy optimization of armored vehicle scheme design, Applied Intelligence 37 (2012) 520-526.
57. Y.J. Zheng, H.F. Ling, Emergency transportation planning in disaster relief supply chain management: a cooperative fuzzy optimization approach, Soft Computing 17 (2013) 1301-1314.