In this work, disjunctive-genetic programming (D-GP), based on the integration of genetic algorithm (GA) with the disjunctive formulations of generalized disjunctive programming (GDP) for the optimization of process networks, has been proposed. Discrete optimization problems, which give rise to the conditional modeling of equations through representations as logic based disjunctions, are very i...

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...

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...

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 proposes a modified non-dominated sorting genetic algorithm (NSGA-II) for a bi-objective location-allocation model. The purpose is to define the best places and capacity of the distribution centers as well as to allocate consumers, in such a way that uncertain consumers demands are satisfied. The objectives of the mixed-integer non-linear programming (MINLP) model are to (1) minimize...

 liquefied natural gas (LNG) is the most economical way of transporting natural gas (NG) over long distances. Liquefaction of NG by using vapor compression refrigeration system requires high operating and capital cost. Due to lack of systematic design methods for multistage refrigeration cycles, the conventional approaches of determining optimal cycle configuration are mostly based on trial-an...

This paper discusses energy savings in wastewater processing plant pump operations and proposes a pump system scheduling model to generate operational schedules to reduce energy consumption. A neural network algorithm is utilized to model pump energy consumption and fluid flow rate after pumping. The scheduling model is a mixed-integer nonlinear programming problem (MINLP). As solving a data-dr...

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

Sudoku, the popular logic puzzle, would have a greater artistic appeal if the final completed puzzle could be transformed into an image similar to nonogram outputs. To do this, we solve a mixed-integer nonlinear programming problem (MINLP) to find the Sudoku configuration that most closely represents a target image via an integer-colour mapping. This alone produces inadequate results, so we rel...

The strategies employed in chromatography steps play a key role in downstream processes for monoclonal antibody (mAb) manufacture. This work addresses the integrated optimisation of chromatography step sequencing and column sizing in mAb purification processes. Chromatography sequencing decisions include the resin selection at each typical step, while the column sizing decisions include the num...