Multi-objective Optimization of Engineering Design Problems Through Pareto-Based Bat Algorithm

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dc.authoridhttps://orcid.org/0000-0002-5229-4018en_US
dc.authoridhttps://orcid.org/0000-0002-7687-9061en_US
dc.authorscopusid36705310900en_US
dc.authorscopusid36728602600en_US
dc.authorwosidG-2829-2015en_US
dc.authorwosidD-7354-2015en_US
dc.contributor.authorÜstün, Deniz
dc.contributor.authorCarbas, Serdar
dc.contributor.authorToktaş, Abdurrahim
dc.date.accessioned2024-08-02T14:11:52Z
dc.date.available2024-08-02T14:11:52Z
dc.date.issued2021en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractAlthough various optimization methods for solving single-objective problems have been developed in the last few decades, these methods have lost their eligibility due to the fact that today’s engineering problems are toward multiple objective optimization problems, in real applications. For single-objective optimization problems, for example, in case of a minimization problem, this value is the decision vector giving the smallest objective that can be achieved within the specified constraints. Hence the minimum decision vector within all possible (feasible) solution vectors is the so-called optimal solution and/or optimal design. However, in multi-objective optimization problems, since a different objective value is generated against each decision vector, the superiority of the solutions over each other is determined by considering the trade-off among the objective values. Therefore, the solution of multi-objective optimization problems, unlike single-objective problems, is a set of vectors rather than a single decision vector. In multi-objective optimization problems, especially if there are intricate objectives, the computational cost of the problem increases. In other words, while synchronously trying to maximize one of the objectives and to minimize another one makes it difficult to find the global optimum design. One of the important techniques used in multi-objective optimization problems is Pareto optimality which enables to select the global optimum solution taking into account the trade-off among all objectives. In this context, using of derivative-based methods has decreased, but the use of metaheuristic methods has increased due to the rapid availability of global optimum solution. This is because the improvements in the field of optimization are progressing in proportion to technology and varying according to the needs. In this chapter, one of the recent metaheuristic optimization methods based on swarm intelligence that is so-called a Pareto-based bat algorithm inspired by the behavior of determining the direction and distance of an object using the echo of the sound called the echolocation of bats is used in order to obtain optimum solutions for multi-objective engineering design problems. In this regard, a four-bar planar truss, a real-sized welded steel beam as well as a multi-layer radar absorber are selected as multi-objective engineering design optimization problems. In case the obtained results (optimal designs) are examined, the potency and the reliability of the proposed multi-objective Pareto-based bat algorithm are demonstrated.en_US
dc.identifier.citationUstun, D., Carbas, S., Toktas, A. (2021). Multi-objective Optimization of Engineering Design Problems Through Pareto-Based Bat Algorithm. Applications of Bat Algorithm and its Variants. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-5097-3_2en_US
dc.identifier.doi10.1007/978-981-15-5097-3_2en_US
dc.identifier.endpage43en_US
dc.identifier.startpage19en_US
dc.identifier.urihttps://doi.org/10.1007/978-981-15-5097-3_2
dc.identifier.urihttps://hdl.handle.net/20.500.13099/326
dc.institutionauthorÜstün, Deniz
dc.language.isoengen_US
dc.publisherSpringer Linken_US
dc.relation.ispartofApplications of Bat Algorithm and its Variantsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_US
dc.titleMulti-objective Optimization of Engineering Design Problems Through Pareto-Based Bat Algorithmen_US
dc.typebookParten_US

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