Homogenous multi-agent optimization for process systems engineering problems with a case study of computer aided molecular design

Abstract

In this paper, we propose a novel homogenous multi-agent optimization (HMAO) framework for optimal design of large scale process system engineering problems. The platform is validated using a benchmark problems and a computer-aided molecular design (CAMD) problem. The molecular design problem is a solvent selection problem and it is formulated as a mixed integer nonlinear programming (MINLP) in which solute distribution coefficient of a candidate solvent is maximized subject to structural feasibility, thermodynamic property and process constraints. The model simultaneously determines the optimal decisions that include the size and the functional groups of the candidate solvents. In developing the HMAO framework, multiple efficient ant colony optimization (EACO) algorithms are considered as distinct algorithmic agents. We illustrate this approach through a real world case study of the optimal design of solvent for extraction of acetic acid from waste process stream using liquid-liquid extraction. The UNIFAC model based on the infinite dilution activity coefficient is used to estimate the mixture properties. The results show that quality of the objective function and the computational efficiencies are improved by a factor ranged from 1.475 to 4.137. The new solvents proposed in this work are with much better targeted thermodynamic properties compared to the solvents proposed so far in previous studies.

Structural Characteristic Integrated Computer-Aided Molecular Design for Phenols Removal Considering Synergistic Effect

“…In Step 4, the selected solvents’ distribution coefficient and solvent loss are calculated, and are ranked in order of decreasing distribution coefficient. UNIFAC group contribution method is usually used for distribution coefficient prediction, − and is described in Supporting Information (eqs S1-S6). In this paper, group parameters consisting of volume parameters, surface area parameters, and interaction parameters are obtained from the liquid–liquid equilibria (LLE) table .…”

Model‐based systems engineering approaches to chemicals and materials manufacturing

“…98 PSE research at molecular level fall under the guise of "computer-aided molecular design" (CAMD), which optimizes chemical synthesis using molecular properties. Application of NDDMs in CAMD includes: solvent selection, [108][109][110] design of molecules, 88,111,112 property predictions, [113][114][115] and fluid dynamics. 116,117 At the process level, process intensification (PI) is the allencompassing topic that covers every aspect of chemical operations.…”

Multiobjective Optimal Controlled Variable Selection for a Gas Turbine–Solid Oxide Fuel Cell System Using a Multiagent Optimization Platform

“…Additionally, should an agent become stuck at local optima, it can glean better results from other agents during this communication session. Readers are referred to ref for a detailed discussion on the MAOP such as information sharing, global optimality, and convergence.…”