This contribution proposes a Mixed Integer Non Linear Programming (MINLP) formulation for optimal design of a catalytic distillation column based on a generic nonequilibrium model (NEQ). The solution strategy for the global optimization combines Simulated Annealing (SA) and Sequential Quadratic Programming (SQP) in order to minimize the objective function. The solution of this MINLP problem yie...

Euclidean norm computations over continuous variables appear naturally in the constraints or in the objective of many problems in the optimization literature, possibly defining non-convex feasible regions or cost functions. When some other variables have discrete domains, it positions the problem in the challenging Mixed Integer Nonlinear Programming (MINLP) class. For any MINLP where the nonli...

Many optimization problems require the modelling of discrete and continuous variables, giving rise to mixed-integer linear and mixed-integer nonlinear programming (MILP / MINLP). An alternative representation of MINLP is Generalized Disjunctive Programming (GDP)1. GDP models are represented through continuous and Boolean variables, and involve algebraic equations, disjunctions, and logic propos...

Mixed Integer Nonlinear Programming (MINLP) problems present two main challenges: the integrality of a subset of variables and nonconvex (nonlinear) objective function and constraints. Many exact solvers for MINLP are branch-and-bound algorithms that compute a lower bound on the optimal solution using a linear programming relaxation of the original problem. In order to solve these problems to o...

this paper uses the weighted l$_1-$norm to propose an algorithm for finding a well-dispersed subset of non-dominated solutions of multiple objective mixed integer linear programming problem. when all variables are integer it finds the whole set of efficient solutions. in each iteration of the proposed method only a mixed integer linear programming problem is solved and its optimal solutions gen...

Optimizing scheduling is an effective way to improve the profit of refineries; it usually requires accurate models to describe the complex and nonlinear refining processes. However, conventional nonlinear models will result in a complex mixed integer nonlinear programming (MINLP) problem for scheduling. This paper presents a piecewise linear (PWL) modeling approach, which can describe global no...

We examine various aspects of modeling and solution via mixedinteger nonlinear programming (MINLP). MINLP has much to offer as a powerful modeling paradigm. Recently, significant advances have been made in MINLP solution software. To fully realize the power of MINLP to solve complex business optimization problems, we need to develop knowledge and expertise concerning MINLP modeling and solution...

A Nonlinear Mixed Integer Programming approach is presented to select the number of membrane modules required in the extraction and stripping sectors of a Non Dispersive Solvent Extraction Plant for effluent treatment and metal recovery. The differential equations that model each membrane module are discretized using orthogonal collocation on finite elements leading to an algebraic system of eq...

This paper uses the L1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (WDSND) vectorsof a multi-objective mixed integer linear programming (MOMILP) problem.The proposed method generalizes the proposed approach by Tohidi and Razavyan[Tohidi G., S. Razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...