A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

An Improved Elite Slime Mould Algorithm for Engineering Design

The Swarm intelligence algorithm is a very prevalent field in which some scholars have made outstanding achievements.As a representative,Slime mould algorithm(SMA)is widely used because of its superior initial performance.Therefore,this paper focuses on the improvement of the SMA and the mitigation of its stagnation problems.For this aim,the structure of SMA is adjusted to develop the efficiency of the original method.As a stochastic optimizer,SMA mainly stimulates the behavior of slime mold in nature.For the harmony of the exploration and exploitation of SMA,the paper proposed an enhanced algorithm of SMA called ECSMA,in which two mechanisms are embedded into the structure:elite strategy,and chaotic stochastic strategy.The details of the original SMA and the two introduced strategies are given in this paper.Then,the advantages of the improved SMA through mechanism comparison,balance-diversity analysis,and contrasts with other counterparts are validated.The experimental results demonstrate that both mechanisms have a significant enhancing effect on SMA.Also,SMA is applied to four structural design issues of the welded beam design problem,PV design problem,I-beam design problem,and cantilever beam design problem with excellent results.

Multiobjective extremal optimization with applications to engineering design

In this paper, we extend a novel unconstrained multiobjective optimization algorithm, so-called multiobjective extremal optimization （MOEO）, to solve the constrained multiobjective optimization problems （MOPs）. The proposed approach is validated by three constrained benchmark problems and successfully applied to handling three multiobjective engineering design problems reported in literature. Simulation results indicate that the proposed approach is highly competitive with three state-of-the-art multiobjective evolutionary algorithms, i.e., NSGA-11, SPEA2 and PAES. Thus MOEO can be considered a good alternative to solve constrained multiobjective optimization problems.

Preliminary Engineering Design of Toroidal Field Magnet System for Superconducting Tokamak HT-7U

HT7U is a large fusion experimental device. It will be built in the Institute of Plasma Physics of Chinese Academy of Sciences. The mission of HT-7U is to develop the scientific basis for a continuously operating tokama-k fusion reactor. This paper describes only a toroidal field (TF) superconducting magnet system of HT7U. In this paper, design criteria of conductor and stability analysis, coil winding and support structure design of magnet system, mechanical calculation and stress analysis, heat load evaluation are given.

CREATIVE DESIGN BASED ON KNOWLEDGE MANAGEMENT IN ENGINEERING DESIGN

To support and serve engineering design, creative design based on knowledge management is proposed. The key knowledge factors of creative design are analyzed and discussed, and knowledge extraction tools are utilized to distill the important knowledge to serve for knowledge resource of creative design. The implementation of creative design mode is described and executed, which can promote the intelligent asset of the enterprise and shorten the period of creative design. With this study, design afflatus and conceptual design can be achieved expediently and effectively.

Process-oriented knowledge-sharing platform for chemical engineering design projects

A process-oriented knowledge-sharing platform is studied to improve knowledge sharing and project management of chemical engineering design enterprises. First, problems and characteristics of knowledge sharing in multi-projects of chemical engineering design are analyzed. Then based on theories of project management, process management, and knowledge management, a process-oriented knowledge-sharing platform is proposed. The platform has three characteristics: knowledge is divided into professional knowledge and project management knowledge; knowledge sharing is integrated with the project process, which makes knowledge sharing a necessary part of the project process and ensures the quantity of knowledge shared; the platform provides quantitative measurements of incentive mechanisms for knowledge providers and users which ensures the quality of knowledge shared. This knowledge-sharing platform uses two knowledge management tools, a knowledge map and a knowledge base, to support the platform.

Investigation into precision engineering design and development of the next-generation brake discs using Al/SiC metal matrix composites

Substantially lightweight brake discs with high wear resistance are highly desirable in the automotive industry.This paper presents an investigation of the precision-engineering design and development of automotive brake discs using nonhomogeneous Al/SiC metal-matrixcomposite materials.The design and development are based on modeling and analysis following stringent precision-engineering principles,i.e.,brake-disc systems that operate repeatably and stably over time as enabled by precision-engineering design.The design and development are further supported by tribological experimental testing and finite-element simulations.The results show the industrial feasibility of the innovative design approach and the application merits of using advanced metal-matrix-composite materials for next-generation automotive and electric vehicles.

Mechanism for Integrating Sustainability in Engineering Design

This paper proposes an integration mechanism to help the owners and designers to integrate sustainability issues into design process, communicate with stakeholders and achieve consensus. Literature concerning engineering design, decision making and environment assessment were reviewed. Sustainability disputes in construction projects were analyzed and owners and designers were interviewed to understand the evolvement of these issues. Key success factors of other successful integration projects were also referenced. An integration mechanism including procedures was established along with traditional design process. Four integration steps were developed： organize integration team, propose integration issues, determine acceptance criteria, and evaluate alternatives; and four integration dimensions were also identified： appeals, decision making and execution, stakeholders, and experts. A matrix was formed by the four integration steps and four dimensions. A rigor index was proposed to measure the quality of the integration process. Finally, the mechanism was tested on a construction project with sustainability controversy to check its validity. The study results show that the integration mechanism can help incorporate sustainability issues and achieve consensus if followed rigorously. The integration matrix systematically examines the eight key integration factors under the four dimensions. The rigor index can explain the quality in integrating sustainability issues into engineering design. The mechanism provides a useful tool for the owners and designers to cope with the sustainability decision making difficulties.

China's Chemical Engineering Design Capability

During the early days of New China, to support the domestic construction of those projects aided by the former Soviet Union, the design institution formed a chemical engineering production installation design team. During the 1950s, this team designed an ammonia synthesis unit with an annual capacity of 75000 tons, set up the Sichuan Chemical Plant and worked out a

Integrated Engineering Design and Data Management

This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling to spatial data management tools. This paper describes how process data, commodities, and location data are disseminated to the various project team members through a central integrated database. The database and 3D model also provide a cache of information that is valuable to the constructor, and operations and maintenance Personnel.

A Multi-strategy Improved Snake Optimizer Assisted with Population Crowding Analysis for Engineering Design Problems

Snake Optimizer(SO)is a novel Meta-heuristic Algorithm(MA)inspired by the mating behaviour of snakes,which has achieved success in global numerical optimization problems and practical engineering applications.However,it also has certain drawbacks for the exploration stage and the egg hatch process,resulting in slow convergence speed and inferior solution quality.To address the above issues,a novel multi-strategy improved SO(MISO)with the assistance of population crowding analysis is proposed in this article.In the algorithm,a novel multi-strategy operator is designed for the exploration stage,which not only focuses on using the information of better performing individuals to improve the quality of solution,but also focuses on maintaining population diversity.To boost the efficiency of the egg hatch process,the multi-strategy egg hatch process is proposed to regenerate individuals according to the results of the population crowding analysis.In addition,a local search method is employed to further enhance the convergence speed and the local search capability.MISO is first compared with three sets of algorithms in the CEC2020 benchmark functions,including SO with its two recently discussed variants,ten advanced MAs,and six powerful CEC competition algorithms.The performance of MISO is then verified on five practical engineering design problems.The experimental results show that MISO provides a promising performance for the above optimization cases in terms of convergence speed and solution quality.

Engineering design and numerical design for chemical looping combustion reactor: A review

Chemical looping combustion(CLC)has emerged as a cost-effective technology for carbon capture at the combustion source.The reactor,being central to the implementation of CLC,primarily adheres to two technological pathways:the dual fluidized bed reactor and the packed bed reactor.However,the intricate interaction between gas-solid reaction flow and heat/mass transfer processes in these reactors gives rise to diverse operational principles at both macroscopic and microscopic levels across various reactor forms and scales,making performance prediction challenging.Consequently,the rational design of CLC reactors poses a significant challenge in advancing this technology to commercial viability.This article offers an extensive review of the prevailing reactor designs in CLC,delving into reactor characteristics,pivotal aspects of the design process,methodologies,and representative studies in the field.The predominant reactor design approaches are categorized into engineering and numerical methods.The former encompasses phenomenological and similarity analysis methods,whereas the latter consists of macroscopic and computational fluid dynamics simulation methods.Each method possesses its theoretical framework,distinctive characteristics,appropriate applications,and respective advantages and limitations.In practical applications,integrating these aspects is essential.For instance,the engineering design,which is less costly but also less precise,is effective for quickly screening numerous potential design scenarios.In contrast,the numerical design,despite its higher computational demand and greater model complexity,offers improved predictive accuracy and is optimal for validating and refining engineering design solutions.

The design and engineering strategies of metal tellurides for advanced metal-ion batteries

Owning various crystal structures and high theoretical capacity,metal tellurides are emerging as promising electrode materials for high-performance metal-ion batteries(MBs).Since metal telluride-based MBs are quite new,fundamental issues raise regarding the energy storage mechanism and other aspects affecting electrochemical performance.Severe volume expansion,low intrinsic conductivity and slow ion diffusion kinetics jeopardize the performance of metal tellurides,so that rational design and engineering are crucial to circumvent these disadvantages.Herein,this review provides an in-depth discussion of recent investigations and progresses of metal tellurides,beginning with a critical discussion on the energy storage mechanisms of metal tellurides in various MBs.In the following,recent design and engineering strategies of metal tellurides,including morphology engineering,compositing,defect engineering and heterostructure construction,for high-performance MBs are summarized.The primary focus is to present a comprehensive understanding of the structural evolution based on the mechanism and corresponding effects of dimension control,composition,electron configuration and structural complexity on the electrochemical performance.In closing,outlooks and prospects for future development of metal tellurides are proposed.This work also highlights the promising directions of design and engineering strategies of metal tellurides with high performance and low cost.

Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems

This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where evaluating the probability value of each fitness is just a computational overhead and contributes nothing to the quality of the alpha or other group members. The fittest dwarf mongoose is selected as the alpha, and a new operator ω is introduced, which controls the alpha movement, thereby enhancing the exploration ability and exploitability of the IDMO. Second, the scout group movements are modified by randomization to introduce diversity in the search process and explore unvisited areas. Finally, the babysitter's exchange criterium is modified such that once the criterium is met, the babysitters that are exchanged interact with the dwarf mongoose exchanging them to gain information about food sources and sleeping mounds, which could result in better-fitted mongooses instead of initializing them afresh as done in DMO, then the counter is reset to zero. The proposed IDMO was used to solve the classical and CEC 2020 benchmark functions and 12 continuous/discrete engineering optimization problems. The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.

An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer Problem

Artificial rabbits optimization(ARO)is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in nature.However,for solving optimization problems,the ARO algorithm shows slow convergence speed and can fall into local minima.To overcome these drawbacks,this paper proposes chaotic opposition-based learning ARO(COARO),an improved version of the ARO algorithm that incorporates opposition-based learning(OBL)and chaotic local search(CLS)techniques.By adding OBL to ARO,the convergence speed of the algorithm increases and it explores the search space better.Chaotic maps in CLS provide rapid convergence by scanning the search space efficiently,since their ergodicity and non-repetitive properties.The proposed COARO algorithm has been tested using thirty-three distinct benchmark functions.The outcomes have been compared with the most recent optimization algorithms.Additionally,the COARO algorithm’s problem-solving capabilities have been evaluated using six different engineering design problems and compared with various other algorithms.This study also introduces a binary variant of the continuous COARO algorithm,named BCOARO.The performance of BCOARO was evaluated on the breast cancer dataset.The effectiveness of BCOARO has been compared with different feature selection algorithms.The proposed BCOARO outperforms alternative algorithms,according to the findings obtained for real applications in terms of accuracy performance,and fitness value.Extensive experiments show that the COARO and BCOARO algorithms achieve promising results compared to other metaheuristic algorithms.

The Application of NURBS Modeling Method to Visualization in Engineering Design

A modeling method is proposed, which combines texture mapping, LOD and geometric modeling. The theory and the application of NURBS in geometric modeling are presented. The methods of NURBS commonly used in the visualization in engineering design are discussed. Some examples are presented.

Application of Monte-Carlo statistical experiments in design of ocean engineering - Estimating the parameters, models and probabilities

Recently, some results have been acquired with the Monte- Carlo statistical experiments in the design of ocean en gineering. The results show that Monte-Carlo statistical experiments can be widely used in estimating the parameters of wave statistical distributions, checking the probability model of the long- term wave extreme value distribution under a typhoon condition and calculating the failure probability of the ocean platforms.

A Structured Methodology for Local Network Design Engineering

This paper presents a structured methodology for local network design engineering (SMLNDE). A complex and fuzzy project for local network design can be decomposed into a set of simple and particular activities using the SMLNDE. The SMLNDE allows rigorous requirements definition and permits the exhaustive consideration of the large number of factors influencing local network design engineering. The complete and clear design documentations and an optimal design can also be provided by the methodology. The SMLNDE has been implemented using the structured analysis and design technique. The study shows that the SMLNDE is an effective design methodology for the large and complex local networks.

Analysis of the Development Strategy of China Petroleum Design ＆ Engineering Company

China Petroleum Design & Engineering Company (CPDEC) is a new corporation established in the year 2001. The company puts forward its development objectives for becoming a first-class national and international desigh firm within 5 to 10 years. In this paper, the theories and techniques related to the business environment and strategy are used to make an analysis of the companys development objectives. According to the analysis of the environment and internal conditions of CPDEC, we suggest adoping the strategic measures for reaching the development objectives on the basis of the SWOT (the acronym of Strengths, Weaknesses, Opportunities and Threats) analysis method. Some conclusions and recommendations on the companys situation and strategies are given.