In this paper the formulation of the optimal design for wheel location of an omnidirectional mobile robot is proposed as an optimization problem. The empirical comparison of the SQP algorithm and eight different DE variants for this particular optimization problems is presented. The importance of using heuristic approaches in real world optimization problem is analyzed via empirical results.

This paper proposes a filter method for solving nonlinear semidefinite programming problems. Our method extends to this setting the filter SQP (sequential quadratic programming) algorithm, recently introduced for solving nonlinear programming problems, obtaining the respective global convergence results. Mathematical subject classification: 90C30, 90C55.

This paper presents hybrid differential evolution DE and sequential quadratic programming SQP for solving the dynamic economic dispatch DED problem for generating units with valvepoint effects. DE is used as a global optimizer and SQP is used as a fine tuning to determine the optimal solution at the final. The feasibility of the proposed method is validated with fiveand ten-unit test systems. R...

We present a class of adaptive multilevel trust-region methods for the efficient solution of optimization problems governed by time–dependent nonlinear partial differential equations with control constraints. The algorithm is based on the ideas of the adaptive multilevel inexact SQP-method from [26, 27]. It is in particular well suited for problems with time–dependent PDE constraints. Instead o...

Transpose-and-Cache Branch-and-Bound (TCBB) has shown promise in solving large single machine quadratic penalty problems. There exist other classes of single machine job sequencing problems which are of more practical importance and which are also of considerable interest in the area of AI search. In the weighted earliness tardiness problem (WET), the best known heuristic estimate is not consis...

Sequential quadratic programming (SQP) methods form a class of highly efficient algorithms for solving nonlinearly constrained optimization problems. Although second derivative information may often be calculated, there is little practical theory that justifies exact-Hessian SQP methods. In particular, the resulting quadratic programming (QP) subproblems are often nonconvex, and thus finding th...