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...

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...

This thesis deals with the development of mathematical models and algorithms for optimizing refinery crude-oil operations schedules. The problem can be posed as a mixed-integer nonlinear program (MINLP), thus combining two major challenges of operations research: combinatorial search and global optimization. First, we propose a unified modeling approach for scheduling problems that aims at brid...

We propose a solution method for a water-network optimization problem using a nonconvex continuous NLP relaxation and an MINLP search. We report successful computational experience using available MINLP software on problems from the literature and on difficult real-world instances.

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...

We are interested in methods to solve mixed-integer nonlinear optimal control problems (MIOCPs) constrained by ordinary differential equations and combinatorial constraints on some of the control functions. To solve these problems we use a first discretize, then optimize approach to get a specially structured mixed-integer nonlinear program (MINLP). We decompose this MINLP into an NLP and an MI...

This paper studies the integration of geological sequestration and microalgae biofixation options for greenhouse gas (GHG) abatement using a supply chain optimisation approach. We propose a multi-scale multi-period mixed-integer nonlinear programming (MINLP) model, which accounts for CO2 transportation pipeline network design, algae processing route and product selection, as well as the seasona...

Structural multiplicity has a significant effect on the solution of an MINLP model for process synthesis problems. The optimization model may also have built-in redundancy that cannot always be directly derived from the multiplicity of the superstructure. A basic GDP representation (BGR) involving logical relations is defined, and can be constructed by applying a standard natural representation...

Employment of unmanned aerial vehicles (UAVs) or drones as swarms coordinating nodes offers multiple advantages for commercial well military applications. However, the complex communication requirements these swarms, coupled with high data rates advanced UAV payloads, require innovative techniques optimizing throughput. Channel capacity being key resource, optimum architecture and network topol...

Purpose – To discuss a new parallel algorithmic platform (minlp_machine) for complex mixed-integer non-linear programming (MINLP) problems. Design/methodology/approach – The platform combines features from classical non-linear optimization methodology with novel innovations in computational techniques. The system constructs discrete search zones around noninteger discrete-valued variables at lo...