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Cited by 16 publications
(14 citation statements)
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“…Hsiao et al [52] proposed an algorithm based on the Einstein's general theory of relativity, which utilized the concept of gravitational field to search for the global optimal solution for a given problem. Ding et al [53] by adding both historical information and defining an adaptive mass enhance the global search ability and accelerate convergence of the simple central force optimization (SCFO) algorithm. Li et al [54] utilized two critical operations including the self-update of reference-group and the interactive-update process between the reference-group and floating-group to find global optimum solutions.…”
Section: Particle Swarm Optimization-based Schedulingmentioning
confidence: 99%
“…Hsiao et al [52] proposed an algorithm based on the Einstein's general theory of relativity, which utilized the concept of gravitational field to search for the global optimal solution for a given problem. Ding et al [53] by adding both historical information and defining an adaptive mass enhance the global search ability and accelerate convergence of the simple central force optimization (SCFO) algorithm. Li et al [54] utilized two critical operations including the self-update of reference-group and the interactive-update process between the reference-group and floating-group to find global optimum solutions.…”
Section: Particle Swarm Optimization-based Schedulingmentioning
confidence: 99%
“…The basic procedures of the original CFO algorithm are as follows: (a) initialization, (b) acceleration calculation, (c) Motion [17].…”
Section: Optimization Model Formulationmentioning
confidence: 99%
“…After obtaining the differential form of the intelligent algorithm (like: Eq. (27)), there are many references applying the linear system theory which is based on the characteristic equations of the differential equations to solve the convergence analysis problems [20][21][22][23]. Based on the linear system theory, the restriction condition to guarantee the system stable is that the spectral radius of the system matrix A(j) stays in the unit circle.…”
Section: Convergence Analysismentioning
confidence: 99%
“…Nature-inspired heuristic optimization algorithms mainly consist of physically-inspired heuristics Xie et al [2011], Ding et al [2012] and biologically-inspired heuristics Kuo et al [2013], Müller et al [2002], Walton et al [2011], Pan [2012], which all have gained widespread popularity in solving complex global optimization problems. In general, these heuristic optimization algorithms suffer somewhat limitations that may give rise to slow convergence or premature to their local optimum.…”
Section: Introductionmentioning
confidence: 99%