Analysis of Weighting and Selection Methods for Pareto-Optimal Solutions of Multiobjective Optimization in Chemical Engineering Applications

A historical review and analysis on MOORA and its fuzzy extensions for different applications

Multi-criteria decision-making (MCDM) methods have been widely used among researchers to provide a trade-off solution between best and worst, considering conflicting criteria and sets of preferences. An efficient and systematic literature review of these methods is needed to maintain their application in distinctive domains. To this end, this paper presents a comprehensive and systematic literature survey on "multi-objective optimization by ratio analysis" (MOORA) method and its fuzzy extensions developed and discussed in recent years. This review includes articles categorized based on the publication name, publishing year, journal name, type of applications, and type of fuzzy extensions. In addition, this review will enhance the understanding of practitioners and decision-makers on the MOORA method, its development, fuzzy hybridization, different application areas, and future work. The study revealed that the MOORA technique was predominantly used with the TOPSIS approach, followed by the AHP and COPRAS methods. Furthermore, 76.28 % use single and hybridization approaches among all MOORA studies, while 23.72 % use MOORA in a fuzzy environment.

Establishment of evaluation system for biological remediation on organic pollution in groundwater using slow-release agents

In situ bioremediation through slow-release agents can continuously degrade organic pollutants for a long time and have high application potential in solving problems such as tailing and rebound. However, the existing evaluation system is difficult to reflect the performance of bioremediation through slow-release agents, which is not conducive to the promotion of technology. It is urgent to establish a targeted evaluation system. Therefore, based on the multi-criteria decision-making method (MCDA), a comprehensive evaluation model was established. The evaluation index system was constructed for bioremediation through slow-release agents consisting of 16 indicators including pollutant degradation rate, agent preparation cost, engineering operation and maintenance cost, secondary pollution, long-term degradation stability, slow release time, slow release stability, increase in functional microbial flora, increase in total DNA content, agent particle size, solid agent morphology, liquid agent viscosity, dispersibility in aqueous phase, zeta potential, operability of agent preparation, and engineering operation management difficulty. Then, the weight of the indicators was determined by using the best-worst method (BWM), and evaluation criteria was established based on relevant norms and literature. Both and the indicators aggregation simple additive weighting (SAW) method constitute a quantitative evaluation model. The above content together constitutes a new evaluation system for biological remediation on organic pollution in groundwater using slow-release agents, which was defined as AOBS evaluation system. In order to verify the rationality and scientificity of the evaluation system, a typical bioremediation slow-release agent was evaluated using the established AOBS evaluation system. The results showed that the evaluation system could reasonably and comprehensively evaluate bioremediation through slow-release agents and provide suggestions for agent improvement.

Proposal for an objective binary benchmarking framework that validates each other for comparing MCDM methods through data analytics

When it comes to choosing the best option among multiple alternatives with criteria of different importance, it makes sense to use multi criteria decision making (MCDM) methods with more than 200 variations. However, because the algorithms of MCDM methods are different, they do not always produce the same best option or the same hierarchical ranking. At this point, it is important how and according to which MCDM methods will be compared, and the lack of an objective evaluation framework still continues. The mathematical robustness of the computational procedures, which are the inputs of MCDM methods, is of course important. But their output dimensions, such as their capacity to generate well-established real-life relationships and rank reversal (RR) performance, must also be taken into account. In this study, we propose for the first time two criteria that confirm each other. For this purpose, the financial performance (FP) of 140 listed manufacturing companies was calculated using nine different MCDM methods integrated with step-wise weight assessment ratio analysis (SWARA). İn the next stage, the statistical relationship between the MCDM-based FP final results and the simultaneous stock returns of the same companies in the stock market was compared. Finally, for the first time, the RR performance of MCDM methods was revealed with a statistical procedure proposed in this study. According to the findings obtained entirely through data analytics, Faire Un Choix Adéquat (FUCA) and (which is a fairly new method) the compromise ranking of alternatives from distance to ideal solution (CRADIS) were determined as the most appropriate methods by the joint agreement of both criteria.

Mathematical Modeling and Robust Multi-Objective Optimization of the Two-Dimensional Benzene Alkylation Reactor with Dry Gas

The benzene alkylation reactor using the dry gas is the most significant equipment in the ethylbenzene manufacturing process. In this paper, a two-dimensional homogeneous model is developed for steady state simulation of the industrial multi-stage catalytic reactor for ethylbenzene. The model validation on a practical benzene alkylation reactor shows the model is accurate and can calculate the hot spot temperatures. The composition of dry gas from upstream process varies with the operating conditions, which can cause unexpected hot spots in the reactor and catalyst deactivation. Considering the uncertainty in dry gas composition, a robust multi-objective optimization framework is proposed: first, the back-off in constraints is introduced to the multi-objective optimization problem to hedge against the worst case; then the optimal operating point can be selected using the multi-criteria decision-making. The reactor optimization objectives are maximizing selectivity of ethylene and conversion of ethylbenzene, and the distribution ratios of dry gas are defined as decision variables. Results of robust multi-objective optimization show the selectivity and conversion at the optimal operating point are 90.88% (decreased by 0.24% compared to the practical condition) and 99.94% (increased by 0.72%). Importantly, the proportion of violations of the hot spot constraints decreases from 13.7% of the traditional method to 3.8% by applying the proposed robust multi-objective optimization method.

Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data

A major difficulty in comparing and even choosing MCDM methods is the uncertainty of information about the consistent and unique characteristics of the results produced. The objective information content of the final scores produced by MCDM methods and their relevance to real life can give us an important idea about them. In this study, first of all, seven MCDM methods with different methodologies were applied to evaluate companies’ financial performance. Then, the obtained MCDM scores were compared using two different objective verification mechanisms. The first validation criterion is the relationship of a MCDM method to real-life rankings (share price). The second criterion is the standard deviation (SD) technique used to discover the objective information content of MCDM final scores. According to the results of this study, PROMETHEE and FUCA definitely outperform other methods in terms of both SD values and strength of correlation with reference real-life rankings. Also, FUCA is methodologically simpler than other methods. However, it produced nearly identical results as the sophisticated PROMETHEE method.

Process Design and Sustainable Development—A European Perspective

This paper describes the state of the art and future opportunities for process design and sustainable development. In the Introduction, the main global megatrends and the European Union’s response to two of them, the European Green Deal, are presented. The organization of professionals in the field, their conferences, and their publications support the two topics. A brief analysis of the published documents in the two most popular databases shows that the environmental dimension predominates, followed by the economic one, while the social pillar of sustainable development is undervalued. The main design tools for sustainability are described. As an important practical case, the European chemical and process industries are analyzed, and their achievements in sustainable development are highlighted; in particular, their strategies are presented in more detail. The conclusions cover the most urgent future development areas of (i) process industries and carbon capture with utilization or storage; (ii) process analysis, simulation, synthesis, and optimization tools, and (iii) zero waste, circular economy, and resource efficiency. While these developments are essential, more profound changes will be needed in the coming decades, such as shifting away from growth with changes in habits, lifestyles, and business models. Lifelong education for sustainable development will play a very important role in the growth of democracy and happiness instead of consumerism and neoliberalism.