A Preference-Based Physical Programming Method for Multi-Objective Designs of Electromagnetic Devices

2020 ◽  
Vol 56 (3) ◽  
pp. 1-4
Author(s):  
Siguang An ◽  
Lei Liu ◽  
Shiyou Yang ◽  
Wei Wang ◽  
Ning Wang
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.


2014 ◽  
Vol 24 ◽  
pp. 341-362 ◽  
Author(s):  
Gilberto Reynoso-Meza ◽  
Javier Sanchis ◽  
Xavier Blasco ◽  
Sergio García-Nieto

2011 ◽  
Vol 63-64 ◽  
pp. 277-280 ◽  
Author(s):  
Hong Zhi Liu ◽  
Li Na Liu

We build up a multi-objective location model of emergency logistics center location, The model combined the construction cost of emergency logistics center with the point of shortest distance from the emergency needs of the logistics center to the limited demand, so that meet the different deployment strategies. We get satisfactory results in the practical by using parametric programming method for solving multi-objective model and verifying for the analysis of examples of this multi-objective decision. The model take into account the cost, efficiency and fairness, combined with the traditional model of coverage (covering model, gravity model and the P-median model).To meet the city's emergency different deployment strategy, the multi-objective location model solve and verify by the parametric programming method and some examples.


2021 ◽  
Vol 19 ◽  
pp. 41-48
Author(s):  
Mona Fuhrländer ◽  
Sebastian Schöps

Abstract. Quantification and minimization of uncertainty is an important task in the design of electromagnetic devices, which comes with high computational effort. We propose a hybrid approach combining the reliability and accuracy of a Monte Carlo analysis with the efficiency of a surrogate model based on Gaussian Process Regression. We present two optimization approaches. An adaptive Newton-MC to reduce the impact of uncertainty and a genetic multi-objective approach to optimize performance and robustness at the same time. For a dielectrical waveguide, used as a benchmark problem, the proposed methods outperform classic approaches.


2019 ◽  
Vol 39 ◽  
pp. 1649-1657
Author(s):  
Tomoaki Yatsuka ◽  
Aya Ishigaki ◽  
Yuki Kinoshita ◽  
Tetsuo Yamada ◽  
Masato Inoue

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