Special Issue "Multi-Objective Optimization of Processes"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Other Topics".

Deadline for manuscript submissions: 28 February 2020.

Special Issue Editors

Guest Editor
Prof. Dr. Gade Pandu Rangaiah Website E-Mail
Department of Chemical and Biomolecular Engineering, National University of Singapore, Block E5, #02-25, 4 Engineering Drive 4, Singapore 117585
Interests: multi-objective optimization techniques and applications to design, process intensification, control, retrofitting and revamping of processes
Guest Editor
Prof. Dr. Andrew Hoadley Website E-Mail
Department of Chemical Engineering, Monash University, Victoria, Australia
Interests: multi-objective optimization techniques and applications to design, process integration, process simulation, sustainability assessment

Special Issue Information

Dear Colleagues,

Optimization has been playing a significant role for designing and controlling improved processes for many decades. However, over recent years, the view of an optimized process has changed from considering just the economic return to include other objectives including environmental impacts, social impacts, process safety, on-stream time, reliability, maintainability, and recyclability, to name just some of the possibilities. When a process designer needs to consider more than one criterion, this is known as multi-criteria decision analysis/making (MCDA/M). Multi-objective optimization (MOO) or optimization for multiple objectives has been a fast developing field of research, because of its ability to identify conflicts between objectives using Pareto-generating techniques that can provide many Pareto-optimal solutions at the same time.

This Special Issue on “Multi-Objective Optimization of Processes” focuses on new developments and applications of MOO to processes and systems of interest to chemical engineers. Topics include but not limited to the following:

  • New techniques for multi-objective optimization;
  • Developments in the selection of Pareto-optimal solutions;
  • Applications to design and control of new processes and systems;
  • Applications to retrofitting/revamping of existing processes and systems;
  • Applications in product design, energy systems, food processing, mineral processing, and drug delivery;
  • Optimization for diverse objectives related to economics, environmental impact, safety, controllability, and/or flexibility.

Prof. Dr. Gade Pandu Rangaiah
Prof. Dr. Andrew Hoadley
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Please note that for papers submitted after 31 December 2019 an APC of 1400 CHF applies. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Optimization of processes for multiple objectives
  • Multi-criteria optimization
  • Multi-criteria decision analysis
  • Process design
  • Process control
  • Process retrofitting
  • Process revamping
  • Industrial processes
  • Energy systems

Published Papers (2 papers)

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Research

Open AccessArticle
Multi-Attribute Decision-Making: Applying a Modified Brown–Gibson Model and RETScreen Software to the Optimal Location Process of Utility-Scale Photovoltaic Plants
Processes 2019, 7(8), 505; https://doi.org/10.3390/pr7080505 - 02 Aug 2019
Abstract
Due to environmental and economic drawbacks of fossil fuels, global renewable energy (RE) capacity has increased significantly over the last decade. Solar photovoltaic (PV) is one of the fastest-growing RE technologies. Selecting an appropriate site is one of the most critical steps in [...] Read more.
Due to environmental and economic drawbacks of fossil fuels, global renewable energy (RE) capacity has increased significantly over the last decade. Solar photovoltaic (PV) is one of the fastest-growing RE technologies. Selecting an appropriate site is one of the most critical steps in utility-scale solar PV planning. This paper aims at proposing a rational multi-criteria decision-making (MCDM) approach based on the Brown–Gibson model for optimal site selection for utility-scale solar PV projects. The proposed model considers the project’s net present value (NPV) along with seven suitability factors and six critical (constraint) factors. The RETScreen software was applied in calculating the NPV, the simple payback period and the carbon emission savings of the project at each alternative site. The weights of the suitability factors were determined using the analytical hierarchy process. Applied to the case study of finding the best location for a 5 MW solar PV project in northern Cameroon, the optimization results showed that Mokolo was the optimal location. The sensitivity analysis results revealed that the rankings of alternative sites based on the project’s NPV and the proposed model are not consistent. Compared to the traditional MCDM approaches, the proposed model provides decision-makers with a more practical thinking method in the optimal location process of utility-scale solar projects. Full article
(This article belongs to the Special Issue Multi-Objective Optimization of Processes)
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Open AccessArticle
Technoeconomic Evaluation of a Process Capturing CO2 Directly from Air
Processes 2019, 7(8), 503; https://doi.org/10.3390/pr7080503 - 02 Aug 2019
Abstract
Capturing CO2 directly from air is one of the options for mitigating the effects global climate change, and therefore determining its cost is of great interest. A process model was proposed and validated using laboratory results for adsorption/desorption of CO2, [...] Read more.
Capturing CO2 directly from air is one of the options for mitigating the effects global climate change, and therefore determining its cost is of great interest. A process model was proposed and validated using laboratory results for adsorption/desorption of CO2, with a branched polyethyleneimine (PEI) loaded mesocellular foam (MCF) silica sorbent. The model was subjected to a Multi-Objective Optimization (MOO) to evaluate the technoeconomic feasibility of the process and to identify the operating conditions which yielded the lowest cost. The objectives of the MOO were to minimize the cost of CO2 capture based on a discounted cash flow analysis, while simultaneously maximizing the quantity of CO2 captured. This optimization identified the minimum cost of capture as 612 USD tonne−1 for dry air entering the process at 25 °C, and 657 USD tonne−1 for air at 22 °C and 39% relative humidity. The latter represents more realistic conditions which can be expected for subtropical climates. The cost of direct air capture could be reduced by ~42% if waste heat was utilized for the process, and by ~27% if the kinetics of the sorbent could be improved by a factor of two. A combination of both would allow cost reductions of ~54%. Full article
(This article belongs to the Special Issue Multi-Objective Optimization of Processes)
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