‎in this paper‎, ‎some kkt type sufficient global optimality conditions‎ ‎for general mixed integer nonlinear programming problems with‎ ‎equality and inequality constraints (minpp) are established‎. ‎we achieve‎ ‎this by employing a lagrange function for minpp‎. ‎in addition‎, ‎verifiable sufficient global optimality conditions for general mixed‎ ‎integer quadratic programming problems are der...

In this paper, we develop heuristics for finding good starting points when solving large-scale nonlinear constrained optimization problems (COPs) formulated as nonlinear programming (NLP) and mixedinteger NLP (MINLP). By exploiting the localities of constraints, we first partition each problem by parallel decomposition into subproblems that are related by complicating constraints and complicati...

This paper presents an approximate multi-parametric nonlinear programming approach to explicit solution of constrained nonlinear model predictive control (MPC) problems in the presence of model uncertainty. The case of time-invariant parameter uncertainty is considered. The explicit MPC controller is based on an orthogonal search tree structure of the state space partition and is designed by so...

In this paper a constrained nonlinear model predictive control (CNMPC) based on deterministic global optimisation is designed. The approach adopted consists in the transformation of the dynamic optimisation problem into a nonlinear programming (NLP) problem using the method of orthogonal collocation on finite elements. Rigorous convex underestimators of the nonconvex NLP problem are then derive...

the product rate variation problem minimizes the variation in the rate at which different models of a common base product are produced on the assembly lines with the assumption of negligible switch-over cost and unit processing time for each copy of each model. the assumption of significant setup and arbitrary processing times forces the problem to be a two phase problem. the first phase determ...

Minimizing the Lennard-Jones potential, the most-studied model problem for molecular conformation, is an unconstrained global optimization problem with a large number of local minima. In this paper, the problem is reformulated as an equality constrained nonlinear programming problem with only linear constraints. This formulation allows the solution to approached through infeasible configuration...

This paper presents an effective optimization method for nonlinear constrained optimization of retaining structures. The proposed algorithm is based on the particle swarm optimization with passive congregation. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the retaining wall. To applying the constraints, the algorithm e...

We give a pattern search method for nonlinearly constrained optimization that is an adaption of a bound constrained augmented Lagrangian method first proposed by Conn, Gould, and Toint [SIAM J. Numer. Anal., 28 (1991), pp. 545–572]. In the pattern search adaptation, we solve the bound constrained subproblem approximately using a pattern search method. The stopping criterion proposed by Conn, Go...