Fuzzy programming method for multi-objective optimal allocation of sediment resources and the cooperative bargaining: a case study in Weishan irrigation area, China

2019 ◽  
Vol 27 (7) ◽  
pp. 7071-7086
Author(s):  
Xianjia Wang ◽  
Ying Qin ◽  
Wenjun Yang ◽  
Suiqiu Yuan
2012 ◽  
Vol 212-213 ◽  
pp. 554-559
Author(s):  
Wen Sheng Dong ◽  
Hui Wang

Optimal allocation problem of water resources has some features that principal and subordinate hierarchical, multi-objective, multi-stage, risk decision-making, etc. Aimed to these characteristics, this paper constructs multiple objective risk decision model under principal and subordinate hierarchical risk decision-making, and by integrating a variety of optimization algorithms for solving idea ( such as fuzzy stochastic simulating technique, multi-objective satisfactory degree computation, principal and subordinate hierarchical game, and evolutionary game solving technology based on particle swarm algorithm), established an algorithm system of possessing logical relations. The result is convincible after a case study.


2021 ◽  
Author(s):  
Ke Zhou

Abstract The standard cuckoo searching algorithm(SCSA)is a population intelligent optimization algorithm, which is also a new heuristic searching algorithm. The advantages of SCSA (such as convenient operation, heuristic searching, etc.) make it easy to find the optimal solution and maintain wider searching range. However, SCSA also has some drawbacks, such as long searching time, easy to fall into local optimum. In order to solve the problems existed in SCSA, in this paper, the improved standard cuckoo searching algorithm (ISCSA) was studied, which includes chaotic initialization and Gaussian disturbed algorithm. As a case study, taking economic, social and ecological benefits as the objective function, the multi-objective water resources optimal allocation models were constructed in Xianxiang Region, China. The ISCSA was applied to solve the water allocation models and the multi-objective optimal water supply scheme for Xinxiang region was obtained. The water resources optimal allocation schemes in the planning level year (2025) for 12 water supply sub-regions were predicted. The desirable eco-environment and benefits were achieved using the studied methods. The results show that the ISCSA has obvious advantages in the solution of water resources optimal allocation and planning.


2019 ◽  
Vol 234 ◽  
pp. 1059-1071 ◽  
Author(s):  
Xianjia Wang ◽  
Ying Qin ◽  
Wenjun Yang ◽  
Suiqiu Yuan ◽  
Kwai-sang Chin

2014 ◽  
Vol 641-642 ◽  
pp. 58-64
Author(s):  
Guo Hua Fang ◽  
Qian Qi Yin ◽  
Xian Feng Huang ◽  
Shuo Xu

With rapid development of society and economy, the issue of water shortage has presently been more and more serious in China. Optimal water and land resources allocation, involving many aspects such as society, economy, ecology etc., is a rational approach to solve this problem. In this study, a substantially improved model, i.e., multi-objective optimal allocation, is established for coordinating the usage of water and land resources. The model was developed on the basis of Immune Genetic Algorithms (IGA), and it mainly includes three objectives and seven constraints. The results of case study show that there is no water shortage in the predicting year of 2020 in Dongtai City, Jiangsu Province by using the optimal allocation of water and land resources. The new optimal allocation proposed in this study has a positive influence to promote the economic and social harmonious development and the natural environment protection for coastal areas of China.


2019 ◽  
Vol 6 (04) ◽  
Author(s):  
ASHUTOSH UPADHYAYA

A study was undertaken in Bhagwanpur distributary of Vaishali Branch Canal in Gandak Canal Command Area, Bihar to optimally allocate land area under different crops (rice and maize in kharif, wheat, lentil, potato in rabi and green gram in summer) in such a manner that maximizes net return, maximizes crop production and minimizes labour requirement employing simplex linear programming method and Multi-Objective Fuzzy Linear Programming (MOFLP) method. Maximum net return, maximum agricultural production, and minimum labour required under defined constraints (including 10% affinity level of farmers to rice and wheat crops) as obtained employing Simplex method were ` 3.7 × 108, 5.06 × 107 Kg and 66,092 man-days, respectively, whereas Multi-Objective Fuzzy Linear Programming (MOFLP) method yielded compromised solution with net return, crop production and labour required as ` 2.4 × 108, 3.3 × 107Kg and 1,79,313 man-days, respectively. As the affinity level of farmers to rice and wheat crops increased from 10% to 40%, maximum net return and maximum production as obtained from simplex linear programming method and MOFLP followed a decreasing trend and minimum labour required followed an increasing trend. MOFLP may be considered as one of the best capable ways of providing a compromised solution, which can fulfill all the objectives at a time.


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