Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems

Fesanghary, M.; Mahdavi, Mehrdad; Minary‐Jolandan, Majid; Alizadeh, Y.

doi:10.1016/j.cma.2008.02.006

Cited by 282 publications

(100 citation statements)

References 25 publications

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“…Musical performance seeks a best state (fantastic harmony) determined by aesthetic estimation, as the optimization process seeks a best state (global optimum: minimum cost; minimum error; maximum benefit; or maximum efficiency) determined by objective function evaluation. Aesthetic estimation is done by the set of the pitches sounded by joined instruments, as objective function evaluation is done by the set of the values produced by composed variables; the aesthetic sounds can be improved practice after practice, as the objective function values can be improved iteration by iteration in [23]. Figure 2 shows the structure of the Harmony Memory (HM) that is the core part of the HS algorithm.…”

Section: The Harmony Search Approachmentioning

confidence: 99%

Efficient harmony search optimization for preventive-maintenance-planning for nuclear power systems

Rami

Hamdaoui

Sayah

et al. 2014

Int. J. Simul. Multidisci. Des. Optim.

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-This paper combines the universal generating function UGF with harmony search (HSO) meta-heuristic optimization method to solve a preventive maintenance (PM) problem for series-parallel system. In this work, we consider the situation where system and its components have several ranges of performance levels. Such systems are called multi-state systems (MSS). To enhance system availability or (reliability), possible schedule preventive maintenance actions are performed to equipments and affect strongly the effective age. The MSS measure is related to the ability of the system to satisfy the demand. The objective is to develop an algorithm to generate an optimal sequence of maintenance actions providing system working with the desired level of availability or (reliability) during its lifetime with minimal maintenance cost rate. To evaluate the MSS system availability, a fast method based on UGF is suggested. The harmony search approach can be applied as an optimization technique and adapted to this PM optimization problem.

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Section: The Harmony Search Approachmentioning

confidence: 99%

Efficient harmony search optimization for preventive-maintenance-planning for nuclear power systems

Rami

Hamdaoui

Sayah

et al. 2014

Int. J. Simul. Multidisci. Des. Optim.

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“…Local search functions can lead to a faster convergence and to more precise results (e.g. [16] or [17]). …”

Section: Hybrid Optimizationmentioning

confidence: 99%

Towards Design Optimization with OpenModelica Emphasizing Parameter Optimization with Genetic Algorithms

Thieriot¹,

Nemer²,

Torabzadeh-Tari³

et al. 2011

Linköping Electronic Conference Proceedings

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One of the main goals when modeling a physical system is to optimize its design or configuration. Currently existing platforms are often dependent on commercial software or are based on in-house and special-purpose development tools. These two alternatives present disadvantages that limit sharing and reusability. The same assessment has partly motivated the origin of the Modelica language itself. In this paper, a new optimization platform called OMOptim is presented. Intrinsically linked with OpenModelica, this platform is mainly aimed at facilitating optimization algorithm development, as well as application use together with models. A first version is already available and three test cases of which one using respectively Dymola and two using OpenModelica are presented. Future developments and design considerations of OMOptim but also of related OpenModelica computation functions are also discussed.

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“…Musical performance seeks a best state (fantastic harmony) determined by aesthetic estimation, as the optimization process seeks a best state (global optimum: minimum cost; minimum error; maximum benefit; or maximum efficiency) determined by objective function evaluation. Aesthetic estimation is done by the set of the pitches sounded by joined instruments, as objective function evaluation is done by the set of the values produced by composed variables; the aesthetic sounds can be improved practice after practice, as the objective function values can be improved iteration by iteration in (Fesanghary et al, 2008). Figure 2 shows the structure of the Harmony Memory (HM) that is the core part of the HS algorithm.…”

Section: The Harmony Search Approachmentioning

confidence: 99%

An Efficient Harmony Search Optimization for Maintenance Planning to the Telecommunication Systems

Harrou¹,

Zeblah²

2011

Search Algorithms and Applications

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Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems

Cited by 282 publications

References 25 publications

Efficient harmony search optimization for preventive-maintenance-planning for nuclear power systems

Efficient harmony search optimization for preventive-maintenance-planning for nuclear power systems

Towards Design Optimization with OpenModelica Emphasizing Parameter Optimization with Genetic Algorithms

An Efficient Harmony Search Optimization for Maintenance Planning to the Telecommunication Systems

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