2021
DOI: 10.1007/s10489-020-02164-7
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Solving microelectronic thermal management problems using a generalized spiral optimization algorithm

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Cited by 9 publications
(4 citation statements)
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“…One of the significant drawbacks of this algorithm is the slow convergence. Therefore, the authors of [29][30][31] have proposed a stochastic SDO algorithm by incorporating some random disturbances at each searching point of the algorithm. Similarly, the authors of [32] have introduced the iterative SDO algorithm for analyzing the information on blurred images.…”
Section: Improved Versions Of Spiral Dynamics Optimization Algorithmmentioning
confidence: 99%
See 2 more Smart Citations
“…One of the significant drawbacks of this algorithm is the slow convergence. Therefore, the authors of [29][30][31] have proposed a stochastic SDO algorithm by incorporating some random disturbances at each searching point of the algorithm. Similarly, the authors of [32] have introduced the iterative SDO algorithm for analyzing the information on blurred images.…”
Section: Improved Versions Of Spiral Dynamics Optimization Algorithmmentioning
confidence: 99%
“…• Micro-channel heat sink [29,30]; • Automation of high-rise buildings [19]; • Planar, spatial truss structures [18]; • Pressure vessel design problems [38,50]; • Welded beam design problems [50].…”
Section: Mechanical Systems Optimizationmentioning
confidence: 99%
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“…Genetic Algorithms [2] and Simulated Annealing [3] are a couple of commonly found examples, which have existed for more than three decades. Others are younger, for example, Reflection-based Optimisation of the Stochastic Spiral Algorithm [4] and Archimedes Optimisation Algorithm [5]. With a rapid literature review, one can notice that innovation in MH has somehow stalled or branched out far from the characteristics that make these methods striking; i.e., hybrids and over-sophisticated approaches.…”
Section: Introductionmentioning
confidence: 99%