NLPQL: a Fortran subroutine for solving constrained nonlinear programming problems. NLPQL is a FORTRAN implementation of a sequential quadratic programming method for solving nonlinearly constrained optimization problems with differentiable objective and constraint functions. At each iteration, the search direction is the solution of a quadratic programming subproblem. This paper discusses the organization of NLPQL, including the formulation of the subproblem and the information that must be provided by a user. A summary is given of the performance of different algorithmic options of NLPQL on a collection of test problems (115 hand-selected or application problems, 320 randomly generated problems). The performance of NLPQL is compared with that of some other available codes.

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  5. Smith, J. MacGregor: Optimal workload allocation in closed queueing networks with state dependent queues (2015)
  6. Sun, Songtao; Zhang, Qiuhua; Loxton, Ryan; Li, Bin: Numerical solution of a pursuit-evasion differential game involving two spacecraft in low earth orbit (2015)
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  16. Schittkowski, K.: A robust implementation of a sequential quadratic programming algorithm with successive error restoration (2011)
  17. Varshney, Rahul; Ahsan, M. J.; Khan, M. G. M.: An optimum multivariate stratified sampling design with nonresponse: a lexicographic goal programming approach (2011)
  18. Xu, Bin; Chen, Nan; Che, Huajun: An integrated method of multi-objective optimization for complex mechanical structure (2010)
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  20. Schittkowski, Klaus: An active set strategy for solving optimization problems with up to 200,000,000 nonlinear constraints (2009)

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