Hybridizing the harmony search algorithm with a spreadsheet ‘Solver’ for solving continuous engineering optimization problems

Ayvaz, M. Tamer; Kayhan, Ali Haydar; Ceylan, Hüseyin; Gürarslan, Gürhan

doi:10.1080/03052150902926835

Cited by 43 publications

(23 citation statements)

References 40 publications

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“…To date, researchers are paying great attention to hybrid approaches to avoid premature convergence toward a local maximum or minimum and reach the global optimum [45]. An example is the hybrid algorithm proposed by Ayvaz et al [46] which requires less iterations and gives more effective results than other deterministic and stochastic optimization algorithms. The issue is that an advanced level of computational and mathematical expertise is required for using hybrid or other optimization algorithms.…”

Section: Discussionmentioning

confidence: 99%

Multiple response optimization: a global criterion‐based method

Costa

Pereira

2010

Journal of Chemometrics

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Processes and products have by nature many quality characteristics that must be in some sense optimized simultaneously. With this aim, a method which can be used easily and efficiently by practitioners for optimizing multi-response problems is proposed. Implementation steps and considerations, in addition to optimization measures to assess method's solutions and guide the analyst in finding an effective compromise solution, are also presented. Three classical examples from the literature are used to assess the performance of several prominent methods in the response surface methodology (RSM) framework and help practitioners make a better-informed choice among them.

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Section: Discussionmentioning

confidence: 99%

Multiple response optimization: a global criterion‐based method

Costa

Pereira

2010

Journal of Chemometrics

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“…In the second way, FCM is used as a further final clustering step to enhance the partitioning results, where it is initialized by the best solution vector improvised in FHSClust. Ayvaz et al (2009) inspired the work of Fesanghary and his colleagues, HS-SQP (Fesanghary et al 2008), explained earlier to propose the same framework but with spreadsheet 'Solver' instead of SQP to improve the results of the HS algorithm in solving continuous engineering optimization problems. Jang et al (2008) are the same like other researchers in this domain that introduced some local search based algorithms into the global search optimization algorithm to improve its performance and increase its convergence speed.…”

Section: Hybridizing Hs With Other Metaheuristic Componentsmentioning

confidence: 91%

The variants of the harmony search algorithm: an overview

2011

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The harmony search (HS) algorithm is a relatively new population-based metaheuristic optimization algorithm. It imitates the music improvisation process where musicians improvise their instruments' pitch by searching for a perfect state of harmony. Since the emergence of this algorithm in 2001, it attracted many researchers from various fields especially those working on solving optimization problems. Consequently, this algorithm guided researchers to improve on its performance to be in line with the requirements of the applications being developed. These improvements primarily cover two aspects: (1) improvements in terms of parameters setting, and (2) improvements in terms of hybridizing HS components with other metaheuristic algorithms. This paper presents an overview of these aspects, with a goal of providing useful references to fundamental concepts accessible to the broad community of optimization practitioners.

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“…These examples have also been solved by other optimization algorithms and the results may be found in Ayvaz et al (2009) and Kayhan et al (2010). Next, the efficiency of SHS is tested for solving sizing optimization of structures for multiple frequency constraints.…”

Section: Pressure Vessel Designmentioning

confidence: 99%

Shape optimization of structures for frequency constraints by sequential harmony search algorithm

Gholizadeh

Barzegar

2013

Engineering Optimization

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Shape optimization of structures with frequency constraints is a highly nonlinear dynamic optimization problem. In order to deal with this type of optimization problem, efficient optimization algorithms should be employed. The main objective of the present study is to propose an efficient harmony search (HS)-based algorithm for solving the shape optimization problem of pin-jointed structures subject to multiple natural frequency constraints. In the proposed algorithm an enhanced version of HS is employed in the framework of the sequential unconstrained minimization technique. The efficiency of the presented sequential harmony search (SHS) algorithm is illustrated through several benchmark optimization examples and the results are compared to those of different optimization techniques. The numerical results demonstrate the computational advantages of the SHS in shape optimization of structures for frequency constraints.

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Hybridizing the harmony search algorithm with a spreadsheet ‘Solver’ for solving continuous engineering optimization problems

Cited by 43 publications

References 40 publications

Multiple response optimization: a global criterion‐based method

Multiple response optimization: a global criterion‐based method

The variants of the harmony search algorithm: an overview

Shape optimization of structures for frequency constraints by sequential harmony search algorithm

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