A new polynomial-time algorithm for linear programming
Combinatorica
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Interior point methods for optimal control of discrete time systems
Journal of Optimization Theory and Applications
Journal of Optimization Theory and Applications
An SQP-type solution method for constrained discrete-time optimal control problems
Computational optimal control
Algorithm 755: ADOL-C: a package for the automatic differentiation of algorithms written in C/C++
ACM Transactions on Mathematical Software (TOMS)
Family of projected descent methods for optimization problems with simple bounds
Journal of Optimization Theory and Applications
Primal-dual interior-point methods
Primal-dual interior-point methods
Iterative Dynamic Programming
An Interior Point Algorithm for Large-Scale Nonlinear Programming
SIAM Journal on Optimization
A globally convergent primal-dual interior-point filter method for nonlinear programming
Mathematical Programming: Series A and B
Line Search Filter Methods for Nonlinear Programming: Motivation and Global Convergence
SIAM Journal on Optimization
Mathematical Programming: Series A and B
Optimization-based approach to path planning for closed chain robot systems
International Journal of Applied Mathematics and Computer Science
| Hi-index | 0.00 |
The main purpose of this paper is to describe the design, implementation and possibilities of our object-oriented library of algorithms for dynamic optimization problems. We briefly present library classes for the formulation and manipulation of dynamic optimization problems, and give a general survey of solver classes for unconstrained and constrained optimization. We also demonstrate methods of derivative evaluation that we used, in particular automatic differentiation. Further, we briefly formulate and characterize the class of problems solved by our optimization classes. The solution of dynamic optimization problems with general constraints is performed by transformation into structured large-scale nonlinear programming problems and applying methods for nonlinear optimization. Two main algorithms of solvers for constrained dynamic optimization are presented in detail: the sequential quadratic programming (SQP) exploring the multistage structure of the dynamic optimization problem during the solution of a sequence of quadratic subproblems, and the nonlinear interior-point method implemented in a general-purpose large-scale optimizer IPOPT. At the end, we include a typical numerical example of the application of the constrained solvers to a large-scale discrete-time optimal control problem and we use the performance profiles methodology to compare the efficiency and robustness of different solvers or different options of the same solver. In conclusions, we summarize our experience gathered during the library development.