We develop and discuss an operational planning model aiming at minimizing production and distribution costs in large drinking water networks containing buffers with free inflow. Modeling drinking water networks is very challenging due of the presence of complex hydraulic constraints, such as friction losses and pump curves. Non-linear, non-convex constraints result from the relationships betwee...

Generalized Disjunctive Programming (GDP) has been introduced recently as an alternative model to MINLP for representing discrete/continuous optimization problems. The basic idea of GDP consists of representing discrete decisions in the continuous space with disjunctions, and constraints in the discrete space with logic propositions. In this paper, we describe a new convex nonlinear relaxation ...

Coordinated voltage and VAR control (VVC) can provide major economic benefits for distribution utilities. Incorporating distributed generations (DG) for VVC can improve the efficiency and reliability of distribution systems. This paper presents an approach to formulate and solve distribution system VVC with DG units as a mixed integer non-linear programming (MINLP) problem. The method can be ut...

Strong branching is an effective branching technique that can significantly reduce the size of the branch-and-bound tree for solving Mixed Integer Nonlinear Programming (MINLP) problems. The focus of this paper is to demonstrate how to effectively use “discarded” information from strong branching to strengthen relaxations of MINLP problems. Valid inequalities such as branching-based linearizati...

This paper addresses the optimal design and planning of sustainable chemical supply chains (SCs) in the presence of uncertainty in the damage model used to evaluate their environmental performance. The environmental damage is assessed through the Eco-indicator 99, which includes the recent advances made in Life Cycle Assessment (LCA). The overall problem is formulated as a bi-criterion stochast...

An algorithm (M-SIMPSA) suitable for the optimization of mixed integer non-linear programming (MINLP) problems is presented. A recently proposed continuous non-linear solver (SIMPSA) is used to update the continuous parameters, and the Metropolis algorithm is used to update the complete solution vector of decision variables. The M-SIMPSA algorithm, which does not require feasible initial points...

We develop a novel superstructure of algal biorefinery processes for biological carbon sequestration and utilization, encompassing off-gas purification, algae cultivation, harvesting and dewatering, lipid extraction, remnant treatment, biogas utilization, and algal oil upgrading stages. Based on the superstructure, we propose a mixed-integer nonlinear programming (MINLP) model to minimize the u...

An optimal design strategy for spiral-wound membrane networks based on an approximate permeator model and a mixedinteger nonlinear programming (MINLP) solution strategy is proposed. A general permeator system superstructure is used to embed a very large number of possible network con®gurations. The superstructure allows the development of a MINLP design strategy which simultaneously optimizes t...

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...

The present study attempts to deal with two problems: optimal allocation of distribution generations (DGs) and reconfiguration a system satisfy several multiobjectives including smoothing the voltage profile, minimizing cost reliability, balancing amount load on end-user side. These problems are merged into one single optimization problem aforementioned objective functions. type is mixed-intege...