Methods for solving nonlinear constraints quadratic programming












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Are there any other methods to solve nonlinear constraints quadratic programming? I have known that some effective numerical methods, i.e, SQP and Gauss pseudospectral method and some heuristic algorithm, i.e, PSO, GA. But I don't know their time complexity, and I also want to know more about other methods and their time complexity.










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    0












    $begingroup$


    Are there any other methods to solve nonlinear constraints quadratic programming? I have known that some effective numerical methods, i.e, SQP and Gauss pseudospectral method and some heuristic algorithm, i.e, PSO, GA. But I don't know their time complexity, and I also want to know more about other methods and their time complexity.










    share|cite|improve this question









    $endgroup$















      0












      0








      0





      $begingroup$


      Are there any other methods to solve nonlinear constraints quadratic programming? I have known that some effective numerical methods, i.e, SQP and Gauss pseudospectral method and some heuristic algorithm, i.e, PSO, GA. But I don't know their time complexity, and I also want to know more about other methods and their time complexity.










      share|cite|improve this question









      $endgroup$




      Are there any other methods to solve nonlinear constraints quadratic programming? I have known that some effective numerical methods, i.e, SQP and Gauss pseudospectral method and some heuristic algorithm, i.e, PSO, GA. But I don't know their time complexity, and I also want to know more about other methods and their time complexity.







      optimization numerical-methods nonlinear-optimization quadratic-programming






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      asked Jan 24 at 3:40









      Zhitao WangZhitao Wang

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          $begingroup$

          Nonlinearly constrained quadratic programming? So you essentially ask about nonlinear programming.



          For that, you use a nonlinear programming algorithm such as interior-point algorithms, penalty methods, SQP, filter methods, etc., and their complexity depends on the method, the problem, properties of the problem, the implementation, etc., i.e. it's impossible to answer generically.



          The fact that the objective is quadratic is not something you typically would explicitly develop solvers for, once the constraints are general nonlinear. In fact, if you allow nonlinear constraints, there is no loss in generality to assume the objective to be linear






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          $endgroup$













          • $begingroup$
            Thank you, I will read more materials abot this topic.
            $endgroup$
            – Zhitao Wang
            Jan 25 at 6:45











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          1 Answer
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          active

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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          2












          $begingroup$

          Nonlinearly constrained quadratic programming? So you essentially ask about nonlinear programming.



          For that, you use a nonlinear programming algorithm such as interior-point algorithms, penalty methods, SQP, filter methods, etc., and their complexity depends on the method, the problem, properties of the problem, the implementation, etc., i.e. it's impossible to answer generically.



          The fact that the objective is quadratic is not something you typically would explicitly develop solvers for, once the constraints are general nonlinear. In fact, if you allow nonlinear constraints, there is no loss in generality to assume the objective to be linear






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            Thank you, I will read more materials abot this topic.
            $endgroup$
            – Zhitao Wang
            Jan 25 at 6:45
















          2












          $begingroup$

          Nonlinearly constrained quadratic programming? So you essentially ask about nonlinear programming.



          For that, you use a nonlinear programming algorithm such as interior-point algorithms, penalty methods, SQP, filter methods, etc., and their complexity depends on the method, the problem, properties of the problem, the implementation, etc., i.e. it's impossible to answer generically.



          The fact that the objective is quadratic is not something you typically would explicitly develop solvers for, once the constraints are general nonlinear. In fact, if you allow nonlinear constraints, there is no loss in generality to assume the objective to be linear






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            Thank you, I will read more materials abot this topic.
            $endgroup$
            – Zhitao Wang
            Jan 25 at 6:45














          2












          2








          2





          $begingroup$

          Nonlinearly constrained quadratic programming? So you essentially ask about nonlinear programming.



          For that, you use a nonlinear programming algorithm such as interior-point algorithms, penalty methods, SQP, filter methods, etc., and their complexity depends on the method, the problem, properties of the problem, the implementation, etc., i.e. it's impossible to answer generically.



          The fact that the objective is quadratic is not something you typically would explicitly develop solvers for, once the constraints are general nonlinear. In fact, if you allow nonlinear constraints, there is no loss in generality to assume the objective to be linear






          share|cite|improve this answer











          $endgroup$



          Nonlinearly constrained quadratic programming? So you essentially ask about nonlinear programming.



          For that, you use a nonlinear programming algorithm such as interior-point algorithms, penalty methods, SQP, filter methods, etc., and their complexity depends on the method, the problem, properties of the problem, the implementation, etc., i.e. it's impossible to answer generically.



          The fact that the objective is quadratic is not something you typically would explicitly develop solvers for, once the constraints are general nonlinear. In fact, if you allow nonlinear constraints, there is no loss in generality to assume the objective to be linear







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited Jan 24 at 13:26

























          answered Jan 24 at 13:17









          Johan LöfbergJohan Löfberg

          5,3101811




          5,3101811












          • $begingroup$
            Thank you, I will read more materials abot this topic.
            $endgroup$
            – Zhitao Wang
            Jan 25 at 6:45


















          • $begingroup$
            Thank you, I will read more materials abot this topic.
            $endgroup$
            – Zhitao Wang
            Jan 25 at 6:45
















          $begingroup$
          Thank you, I will read more materials abot this topic.
          $endgroup$
          – Zhitao Wang
          Jan 25 at 6:45




          $begingroup$
          Thank you, I will read more materials abot this topic.
          $endgroup$
          – Zhitao Wang
          Jan 25 at 6:45


















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