BACKGROUND In this study, bio-inspired computing is exploited for solving system of nonlinear equations using variants of genetic algorithms (GAs) as a tool for global search method hybrid with sequential quadratic programming (SQP) for efficient local search. The fitness function is constructed by defining the error function for systems of nonlinear equations in mean square sense. The design p...

In this paper, by combining the splitting method of augmented Lagrange function (ALF) with sequential quadratic programming (SQP) approximation, a novel ALF-based algorithm SQP structure is proposed for multi-block linear constrained nonconvex separable optimization. The new uses idea to decompose original problem into several small-scale subproblems. Meanwhile, approximation and Armijo-type li...

We consider optimization problems with objective and constraint functions that may be nonconvex and nonsmooth. Problems of this type arise in important applications, many having solutions at points of nondifferentiability of the problem functions. We present a line search algorithm for situations when the objective and constraint functions are locally Lipschitz and continuously differentiable o...

We propose a method for constrained and unconstrained nonlinear multiobjective optimization problems that is based on an SQP-type approach. The proposed algorithm maintains a list of nondominated points that is improved both for spread along the Pareto front and optimality by solving single-objective constrained optimization problems. These single-objective problems are derived as SQP problems ...

In this paper we propose a merit function piecewise SQP algorithm for solving mathematical programs with equilibrium constraints (MPECs) formulated as mathematical programs with complementarity constraints. Under some mild conditions, the new algorithm is globally convergent to a piecewise stationary point. Moreover if the partial MPECLICQ is satisfied at the accumulation point then the accumul...

This paper presents an approach to the design of optimal control strategy for plug-in hybrid electric vehicles (PHEVs) incorporating Internet Vehicles (IoVs). The is designed and implemented by employing a mobile edge computing (MEC) based framework IoVs. thresholds in can be instantaneously optimized chaotic particle swarm optimization with sequential quadratic programming (CPSO-SQP) units (ME...

An approach for the construction of optimal analog wavelet bases is presented. First, the definition of an analog wavelet is given. Based on the definition and the least-squares error criterion, a general framework for designing optimal analog wavelet bases is established, which is one of difficult nonlinear constrained optimization problems. Then, to solve this problem, a hybrid algorithm by c...

In his 1963 PhD thesis, Wilson proposed the first sequential quadratic programming (SQP) method for the solution of constrained nonlinear optimization problems. In the intervening 48 years, SQP methods have evolved into a powerful and effective class of methods for a wide range of optimization problems. We review some of the most prominent developments in SQP methods since 1963 and discuss the ...