Solving the Static Manycast RWA Problem in Optical Networks Using Evolutionary Programming

Zakouni, Amiyne; Luo, Jiawei; Kharroubi, Fouad

doi:10.1007/978-3-319-42294-7_12

Cited by 4 publications

(1 citation statement)

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“…Therefore, GA requires tuning to determine an appropriate combination of parameters. More details about GA can be found in [30,[33][34][35]. The SCE-UA employs a process called competitive complex evolution (CCE) algorithm to search for a global optimization (Figure 1b).…”

Section: Introductionmentioning

confidence: 99%

A Dynamically Dimensioned Search Allowing a Flexible Search Range and Its Application to Optimize Discrete Hedging Rule Curves

Jin

Lee

Kang

et al. 2022

Water

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The discrete hedging rule for reservoir operation includes time-varying trigger volumes used for the onset and termination of water rationing, which complicates its optimization problems. A dynamically dimensioned search can be easily applied to complex optimization problems, but the performance is relatively limited in constrained optimization problems such as deriving reservoir operation rules. A dynamically dimensioned search allowing for a flexible search range is proposed in this study to efficiently solve constrained optimization problems. The modified algorithm can recursively update the search ranges of decision variables with limited overlaps. The above two algorithms are applied to derive hedging rule curves for three reservoirs. Objective function values are closely converged to optimum solutions, with fewer evaluations using the modified algorithm than those using the traditional algorithm. The modified algorithm restrains an overlapped search range of decision variables and can reduce redundant computational efforts caused by unreasonable candidate solutions that violate inequality conditions.

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Section: Introductionmentioning

confidence: 99%