A solving approach for fuzzy multi-objective linear fractional programming and application to an agricultural planting structure optimization problem

In this paper, an algorithm is presented to solve fuzzy multi-objective linear fractional programming (FMOLFP) problems through an approach based on superiority and inferiority measures method (SIMM). In the model for the proposed approach, each of fuzzy goals defined for the fractional objectives a...

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Vydáno v:Chaos, solitons and fractals Ročník 141; s. 110352
Hlavní autoři: Yang, Gaiqiang, Li, Xia, Huo, Lijuan, Liu, Qi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.12.2020
Témata:
Fuzzy programming
Goal programming
Multi-objective linear fractional programming
Planting structure
Superiority and inferiority measures
Multi-objective linear fractional programming
Fuzzy programming
Superiority and inferiority measures
Planting structure
Goal programming
ISSN:0960-0779, 1873-2887
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Shrnutí:In this paper, an algorithm is presented to solve fuzzy multi-objective linear fractional programming (FMOLFP) problems through an approach based on superiority and inferiority measures method (SIMM). In the model for the proposed approach, each of fuzzy goals defined for the fractional objectives and some of constraints have fuzzy numbers. To achieve the highest membership value, SIMM is adopted to deal with fuzzy number in constraints, then a linear goal programming methodology is introduced to solve the problem in which the fractional objectives is fuzzy goals. A case of agricultural planting structures optimization problem is solved to illustrate the application of the algorithm. The results show that winter wheat and summer corn acreage should be 38,386.4 ha, and cotton acreage should be 20,669.6 ha. Because of high risk in cotton cultivation at present, the ratio of grain planted area to cotton planted area is unreasonable. An improved support in policy is necessary for the government to enhance the enthusiasm of farmers to plant cotton and sustain the development of cotton market in the long term.
ISSN:0960-0779
1873-2887
DOI:10.1016/j.chaos.2020.110352