The loading pattern of fuel bundles in a reactor core determines the characteristics of the reloading cycle. The problem of maximizing fuel utilization during a cycle may be formulated as a nonlinear mixed integer programming (NLMIP) problem, and has until now mostly been treated by heuristic optimization methods like simulated annealing. This paper evalutes the performance of state-of-the-art ...

In this article we look at a new algorithm for solving convex mixed integer nonlinear programming problems. The algorithm uses an integrated approach, where a branch and bound strategy is mixed with solving nonlinear programming problems at each node of the tree. The nonlinear programming problems, at each node, are not solved to optimality, rather one iteration step is taken at each node and t...

This paper is about a computer application for planning maintenance of aircraft fleet in what regards allocation skilled technicians. The formalization this mathematical programming problem written as minimizing one. decision variables are the data number available technicians, working hours needed to accomplish maintenance, costs due daily operation facilities, and downtime. Although, non-line...

In the context of convex mixed integer nonlinear programming (MINLP), we investigate how the outer approximation method and the generalized Benders decomposition method are affected when the respective nonlinear programming (NLP) subproblems are solved inexactly. We show that the cuts in the corresponding master problems can be changed to incorporate the inexact residuals, still rendering equiv...

 We consider a generalization of the classical quadratic assignment problem, where coordinates of locations are uncertain and only upper and lower bounds are known for each coordinate. We develop a mixed integer linear programming model as a robust counterpart of the proposed uncertain model. A key challenge is that, since the uncertain model involves nonlinear objective function of the ...

Optimization as an enabling technology has been one of the big success stories in process systems engineering. In this paper we present first a general review of optimization and its applications to a variety of problems in process systems engineering. Next, we provide an overview of two key areas: nonlinear programming and logic-based discrete/continuous optimization. In particular, recent adv...

We propose a modified sequential quadratic programming (SQP) method for solving mixed-integer nonlinear programming problems. Under the assumption that integer variables have a smooth influence on the model functions, i.e., that function values do not change drastically when inor decrementing an integer value, successive quadratic approximations are applied. The algorithm is stabilized by a tru...