A Discrete Biogeography-Based Optimization for Solving Tomato Planting Planning

被引：5

作者：

Zhang, Hong-li ^{[1
]}

Wang, Cong ^{[1
]}

机构：

[1] Xinjiang Univ, Sch Elect Engn, Urumqi 830047, Peoples R China

来源：

INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2016, PT II | 2016年 / 9772卷

关键词：

Balanced supply; Discrete biogeography-based optimization; Matrix compression method; Tomato planting planning; ALGORITHM;

D O I：

10.1007/978-3-319-42294-7_68

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The yield of tomato affects the processing ability of ketchup factory directly. To improve the imbalance supply of the materials during tomato sauce season, building the mathematical model of tomato planting planning, a discrete Biogeography-based Optimization is proposed for solving tomato planting planning model. Considering the tomato planting planning is a large-scale combinatorial optimization problem, tomato planting matrix can be compressed by sparse matrix compression method to achieve compression of the solution space. And a new kind discrete BBO with a new coding way was used for planting planning. A tomato plant provides data in Xinjiang as an example of simulation calculation, the results showed that tomato planting planning scheme calculated by the proposed algorithm can realize the balance supplement of tomato materials effectively.

引用

页码：770 / 781

页数：12

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