Abstract A method of Sequential Log-Convex Programming (SLCP) is constructed that exploits the log-convex structure present in many engineering design problems. The mathematical Geometric (GP) combined with ability Quadratic Program (SQP) to accommodate a wide range objective and constraint functions, resulting practical algorithm can be adopted little no modification existing practices. Three ...

This paper is concerned with a Superlinearly feasible SQP algorithm algorithm for general constrained optimization. As compared with the existing SQP methods, it is necessary to solve equality constrained quadratic programming sub-problems at each iteration, which shows that the computational effort of the proposed algorithm is reduced further. Furthermore, under some mild assumptions, the algo...

Asset allocation is critical for the portfolio management process. In this paper, we solve a dynamic asset allocation problem through a multiperiod stochastic programming model. The objective is to maximise the expected utility of wealth at the end of the planning periods. To improve the optimisation result of the model, we employ swarm intelligent optimisers, the Bacterial Foraging Optimisatio...

A sequential quadratic programming (SQP) algorithm generating feasible iterates is described and analyzed. What distinguishes this algorithm from previous feasible SQP algorithms proposed by various authors is a reduction in the amount of computation required to generate a new iterate while the proposed scheme still enjoys the same global and fast local convergence properties. A preliminary imp...

Muscle forces during locomotion are often predicted using static optimisation and SQP. SQP has been criticised for over-estimating force magnitudes and under-estimating co-contraction. These problems may be related to SQP's difficulty in locating the global minimum to complex optimisation problems. Algorithms designed to locate the global minimum may be useful in addressing these problems. Musc...

Successive Quadratic Programming (SQP) has been the method of choice for the solution of many nonlinear programming problems in process engineering. However, for the solution of large problems with SQP based codes, the combinatorial complexity associated with active set quadratic programming (QP) methods can be a bottleneck in exploiting the problem structure. In this paper, we examine the meri...

QPCOMP is an extremely robust algorithm for solving mixed nonlinear complementarity problems that has fast local convergence behavior. Based in part on the NE/SQP method of Pang and Gabriell14], this algorithm represents a signiicant advance in robustness at no cost in eeciency. In particular, the algorithm is shown to solve any solvable Lipschitz continuous, continuously diierentiable, pseudo-...