scholarly journals Design of super-elliptical gradient coils based on multiple objective Pareto optimization method

2017 ◽  
Vol 66 (9) ◽  
pp. 098301
Author(s):  
Pan Hui ◽  
Wang Liang ◽  
Wang Qiang-Long ◽  
Chen Li-Min ◽  
Jia Feng ◽  
...  
Author(s):  
CHAOFANG HU ◽  
SHAOYUAN LI

This paper proposes an enhanced interactive satisfying optimization method based on goal programming for the multiple objective optimization problem with preemptive priorities. Based on the previous method, the approach presented makes the higher priority achieve the higher satisfying degree. For three fuzzy relations of the objective functions, the corresponding optimization models are proposed. Not only can satisfying results for all the objectives be acquired, but the preemptive priority requirement can also be simultaneously actualized. The balance between optimization and priorities is realized. We demonstrate the power of this proposed method by illustrative examples.


2015 ◽  
Vol 2015 (0) ◽  
pp. _J1030205--_J1030205- ◽  
Author(s):  
Yuki MIMURA ◽  
Masayuki ICHIMONJI ◽  
Kyohei HIRAI ◽  
Toshikazu NAGATA ◽  
Toshiaki HIRATE ◽  
...  

2020 ◽  
Vol 9 (2) ◽  
pp. 1-30
Author(s):  
Navee Chiadamrong ◽  
Noppasorn Sutthibutr

This study uses an integrated optimization method by applying a weighted additive multiple objective linear model with Possibilistic Linear Programming (PLP) to fuzzy Aggregate Production Planning (APP) problems under an uncertain environment. The uncertainty conditions include uncertainties of operating times and costs, customer demand, labor level, as well as machine capacity. The aim of this study is to minimize total costs of the plan that consist of the production cost and costs of changes in labor level. The proposed hybrid approach minimizes the most possible value of the imprecise total costs, maximizes the possibility of obtaining lower total costs, and minimizes the risk of obtaining higher total costs from PLP as multiple objectives for the fuzzy multiple objective linear model optimization. The outcome of the proposed approach shows that the solution is closer to the ideal solution obtained from Linear Programming than a typical solution obtained from PLP. There is also a higher overall satisfaction value.


Author(s):  
CHAOFANG HU ◽  
SHAOYUAN LI

This paper presents a two-phase interactive satisfying optimization method for fuzzy multiple objectives optimization with linguistic preference. This proposed approach utilizes the view that the more important objective has the higher desirable satisfying degree. The originally complex optimization problem is simplified and divided into two parts that are solved one by one. The decision maker can acquire satisfying solution of all the objectives under linguistic preference. Numerical example shows the efficiency, flexibility, and sensitivity of the proposed method.


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