scholarly journals Applications of Multi-Objective Optimization to Industrial Processes: A Literature Review

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 133
Author(s):  
Sandra C. Cerda-Flores ◽  
Arturo A. Rojas-Punzo ◽  
Fabricio Nápoles-Rivera

Industrial processes provide several of the products and services required for society. However, each industry faces different challenges from different perspectives, all of which must be reconciled to obtain profitable, productive, controllable, safe and sustainable processes. In this context, multi-objective optimization has become a powerful tool to aid the decision-making mechanism in the synthesis, design, operation and control of such processes. The solution to the mathematical models provides the necessary tools to asses the system performance in terms of different metrics and evaluate the trade-offs between the objectives in conflict. The number of applications of multi- objective optimization in industrial processes is ample and each application has its own challenges. In the present literature review, a broad panorama of the applications in multi-objective optimization is presented, including future perspectives and open questions that still need to be addressed.

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4466
Author(s):  
Maël Riou ◽  
Florian Dupriez-Robin ◽  
Dominique Grondin ◽  
Christophe Le Loup ◽  
Michel Benne ◽  
...  

Microgrids operating on renewable energy resources have potential for powering rural areas located far from existing grid infrastructures. These small power systems typically host a hybrid energy system of diverse architecture and size. An effective integration of renewable energies resources requires careful design. Sizing methodologies often lack the consideration for reliability and this aspect is limited to power adequacy. There exists an inherent trade-off between renewable integration, cost, and reliability. To bridge this gap, a sizing methodology has been developed to perform multi-objective optimization, considering the three design objectives mentioned above. This method is based on the non-dominated sorting genetic algorithm (NSGA-II) that returns the set of optimal solutions under all objectives. This method aims to identify the trade-offs between renewable integration, reliability, and cost allowing to choose the adequate architecture and sizing accordingly. As a case study, we consider an autonomous microgrid, currently being installed in a rural area in Mali. The results show that increasing system reliability can be done at the least cost if carried out in the initial design stage.


Author(s):  
Cristina Johansson ◽  
Johan Ölvander ◽  
Micael Derelöv

In early design phases, it is vital to be able to screen the design space for a set of promising design alternatives for further study. This article presents a method able to balance several objectives of different mathematical natures, with high impact on the design choices. The method (MOSART) handles multi-objective optimization for safety and reliability trade-offs. The article focuses on optimization problem approach and processing of results as a base for decision-making. The output of the optimization step is the selection of specific system elements obtaining the best balance between the targets. However, what is a good base for decision can easily transform into too much information and overloading of the decision-maker. To solve this potential issue, from a set of Pareto optimal solutions, a smaller sub-set of selected solutions are visualized and filtered out using preference levels of the objectives, yielding a solid base for decision-making and valuable information on potential solutions. Trends were observed regarding each system element and discussed while processing the results of the analysis, supporting the decision of one final best solution.


Author(s):  
Huizhuo Cao ◽  
Xuemei Li ◽  
Vikrant Vaze ◽  
Xueyan Li

Multi-objective pricing of high-speed rail (HSR) passenger fares becomes a challenge when the HSR operator needs to deal with multiple conflicting objectives. Although many studies have tackled the challenge of calculating the optimal fares over railway networks, none of them focused on characterizing the trade-offs between multiple objectives under multi-modal competition. We formulate the multi-objective HSR fare optimization problem over a linear network by introducing the epsilon-constraint method within a bi-level programming model and develop an iterative algorithm to solve this model. This is the first HSR pricing study to use an epsilon-constraint methodology. We obtain two single-objective solutions and four multi-objective solutions and compare them on a variety of metrics. We also derive the Pareto frontier between the objectives of profit and passenger welfare to enable the operator to choose the best trade-off. Our results based on computational experiments with Beijing–Shanghai regional network provide several new insights. First, we find that small changes in fares can lead to a significant improvement in passenger welfare with no reduction in profitability under multi-objective optimization. Second, multi-objective optimization solutions show considerable improvements over the single-objective optimization solutions. Third, Pareto frontier enables decision-makers to make more informed decisions about choosing the best trade-offs. Overall, the explicit modeling of multiple objectives leads to better pricing solutions, which have the potential to guide pricing decisions for the HSR operators.


2019 ◽  
Vol 11 (23) ◽  
pp. 6728 ◽  
Author(s):  
Zhang ◽  
Huang ◽  
Liu ◽  
Li

High-efficiency taxiing for safe operations is needed by all types of aircraft in busy airports to reduce congestion and lessen fuel consumption and carbon emissions. This task is a challenge in the operation and control of the airport’s surface. Previous studies on the optimization of aircraft taxiing on airport surfaces have rarely integrated waiting constraints on the taxiway into the multi-objective optimization of taxiing time and fuel emissions. Such studies also rarely combine changes to the airport’s environment (such as airport elevation, field pressure, temperature, etc.) with the multi-objective optimization of aircraft surface taxiing. In this study, a multi-objective optimization method for aircraft taxiing on an airport surface based on the airport’s environment and traffic conflicts is proposed. This study aims to achieve a Pareto optimized taxiing scheme in terms of taxiing time, fuel consumption, and pollutant emissions. This research has the following contents: (1) Previous calculations of aircraft taxiing pathways on the airport’s surface have been based on unimpeded aircraft taxiing. Waiting on the taxiway is excluded from the multi-objective optimization of taxiing time and fuel emissions. In this study, the waiting points were selected, and the speed curve was optimized. A multi-objective optimization scheme under aircraft taxiing obstacles was thus established. (2) On this basis, the fuel flow of different aircraft engines was modified with consideration to the aforementioned environmental airport differences, and a multi-objective optimization scheme for aircraft taxiing under different operating environments was also established. (3) A multi-objective optimization of the taxiing time and fuel consumption of different aircraft types was realized by acquiring their parameters and fuel consumption indexes. A case study based on the Shanghai Pudong International Airport was also performed in the present study. The taxiway from the 35R runway to the 551# stand in the Shanghai Pudong International Airport was optimized by the non-dominant sorting genetic algorithm II (NSGA-II). The taxiing time, fuel consumption, and pollutant emissions at this airport were compared with those of the Kunming Changshui International Airport and Lhasa Gonggar International Airport, which have different airport environments. Our research conclusions will provide the operations and control departments of airports a reference to determine optimal taxiing schemes.


2020 ◽  
Vol 10 (3) ◽  
pp. 22
Author(s):  
Andy D. Pimentel

As modern embedded systems are becoming more and more ubiquitous and interconnected, they attract a world-wide attention of attackers and the security aspect is more important than ever during the design of those systems. Moreover, given the ever-increasing complexity of the applications that run on these systems, it becomes increasingly difficult to meet all security criteria. While extra-functional design objectives such as performance and power/energy consumption are typically taken into account already during the very early stages of embedded systems design, system security is still mostly considered as an afterthought. That is, security is usually not regarded in the process of (early) design-space exploration of embedded systems, which is the critical process of multi-objective optimization that aims at optimizing the extra-functional behavior of a design. This position paper argues for the development of techniques for quantifying the ’degree of secureness’ of embedded system design instances such that these can be incorporated in a multi-objective optimization process. Such technology would allow for the optimization of security aspects of embedded systems during the earliest design phases as well as for studying the trade-offs between security and the other design objectives such as performance, power consumption and cost.


2019 ◽  
Vol 71 (6) ◽  
pp. 766-771 ◽  
Author(s):  
Xiuying Wang ◽  
Michael Khonsari ◽  
Siyuan Li ◽  
Qingwen Dai ◽  
Xiaolei Wang

Purpose This study aims to simultaneously enhance the load-carrying capacity and control the leakage rate of mechanical seals by optimizing the texture shape. Design/methodology/approach A multi-objective optimization approach is implemented to determine the optimal “free-form” textures and optimal circular dimples. Experiments are conducted to validate the simulation results. Findings The experimental coefficient of friction (COF) and leakage rate are in good agreement with the calculated results. In addition, the optimal “free-form” texture shows a lower COF and a lower leakage in most cases. Originality/value This work provides a method to optimize the surface texture for a better combination performance of mechanical seals.


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