MINLP problems are hard constrained optimization problems, with nonlinear constraints and mixed discrete continuous variables. They can be solved using a Branch-and-Bound scheme combining several methods, such as linear programming, interval analysis, and cutting methods. Our goal is to integrate constraint programming techniques in this framework. Firstly, global constraints can be introduced ...

Mathematical programming has long been recognized as a promising direction to the efficient solution of design, synthesis and operation problems that can gain industry the competitive advantage required to survive in today’s difficult economic environment. Most of the engineering design problems can be modeled as MINLP problems with stochastic parameters. In this paper a novel decomposition alg...

This paper treats the solution of nonlinear optimization problems involving discrete decision variables, also known as generalized disjunctive programming (GDP) or mixed-integer nonlinear programming (MINLP) problems, that arise in process engineering. The key idea is to eliminate the discrete decision variables by adding a set of continuous variables and constraints that represent the discrete...

In a highly competitive scenario, suppliers play a vital role in making a business organization successful. Business of any organization is continuous process and therefore the supplier selection is also dynamic in nature. This is quite natural as the organization’s demand; supplier’s capacity, quality level, lead time, unit part cost and fixed transportation cost of supplier varies with time. ...

Discrete-continuous non-linear optimization models are frequently used to formulate problems in process system engineering. Major modeling alternatives and solution algorithms include generalized disjunctive programming and mixed integer non-linear programming (MINLP). Both have advantages and drawbacks depending on the problem they are dealing with. In this work, we describe the theory behind ...

The analytical target cascading (ATC) optimization technique for hierarchical systems demonstrates convergence properties only under assumptions of convexity and continuity. Many practical engineering design problems, however, involve a combination of continuous and discrete variables resulting in the development of mixed integer nonlinear programming (MINLP) formulations. While ATC has been ap...

We consider a production planning problem where the production process creates a mixture of desirable products and undesirable byproducts. In this production process, at any point in time the fraction of the mixture that is an undesirable byproduct increases monotonically as a function of the cumulative mixture production up to that time. The mathematical formulation of this continuous-time pro...

Aircraft conflict avoidance is a critical issue in Air Traffic Management, which can be addressed, among others, by means of Mixed Integer Non-Linear Programming (MINLP) techniques. In this work we introduce a new approach to address, via velocity regulation, the problem of avoiding conflict for a set of aircraft flying in an air sector at cruise flight. Speed variations for all aircraft are to...

This article presents the formulation and the solution of a class of Mixed-integer Nonlinear Programming (MINLP) problems, applied to optimal synthesis of process systems in a modular simulator environment. The proposed algorithm makes use of module, reduces the work of calculation on model equations, makes the size of MINLP smaller. The algorithm consists of solving alternate sequences of MILP...

In this work we present an Outer-Approximation algorithm to obtain the global optimum of a nonconvex Mixed Integer Nonlinear Programming (MINLP) model for the scheduling of crude oil movement at the front-end of a petroleum refinery. The model relies on a continuous time representation making use of transfer events. The proposed technique focuses on effectively solving a Mixed Integer Linear Pr...