Rotated-cone-programming method for designing phase-equalization system

Author(s):  
Noboru Ito ◽  
Wei Qin
Author(s):  
Xiang Zhou ◽  
Hong-Bo Zhang ◽  
Lei Xie ◽  
Guo-Jian Tang ◽  
Wei-Min Bao

The maximum-crossrange problem is difficult to solve rapidly and stably because of highly nonlinear dynamics and nonconvex constraints. In this paper, an improved successive second-cone programming method via the pole-transformation process is proposed. The main contribution of this work is twofold. Firstly, the pole-transformation coordinate frame is defined, and the original problem is reformulated by the pole-transformation process to avoid the linearization of downrange and crossrange angles. The terminal state constraint is relaxed to an inequality constraint, which improves the stability performance of the solution method. Secondly, an adaptively adjustment method of the trust-region contraction coefficient is proposed to improve the convergence performance of the solution method. The optimal solution of the original problem is obtained by the improved successive second-order cone programming method. The numerical experiments verify the effectiveness of the pole-transformation process, and the convergence and stability performances of the improved solution method proposed in this paper.


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.


2022 ◽  
Vol 73 ◽  
pp. 102238
Author(s):  
Chen Zheng ◽  
Yushu An ◽  
Zhanxi Wang ◽  
Haoyu Wu ◽  
Xiansheng Qin ◽  
...  

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