Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement

Sait, Sadiq M.; Ali, Mustafa Imran; Zaidi, Ali Mustafa

doi:10.1007/s10852-007-9064-7

Cited by 6 publications

(1 citation statement)

References 11 publications

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“…SimE has been applied to a variety of optimization problems such as very large scale integration (VLSI) [2], [3], [4], [5], field programmable gate array (FPGA) design [6], signal processing [7], the driver scheduling problem [8], the set covering problem [9], operand data type problem [10], task matching and scheduling [11], routing in computer networks [12], and LAN topology design [13], [14]. However, no recent attempt has been made to investigate the effect of the evaluation step on the quality of the solution, and what should be the structure or characteristics of the evaluation function.…”

Section: Discussionmentioning

confidence: 99%

Assessment of the “Evaluation” function in the simulated evolution algorithm

Khan

Engelbrecht

2011

2011 Seventh International Conference on Natural Computation

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Simulated Evolution is a stochastic evolutionary search strategy. The algorithm repeatedly executes evaluation, selection, and allocation steps in a sequence, until certain stopping conditions are met. The evaluation step assesses the quality of each individual element of a solution with respect to a single or multiple attributes. The outcome of this step, combined with the results of the selection step, play an important role during the allocation step, where the existing solution is perturbed to generate a new solution. This paper attempts to study the effect of the evaluation step on the quality of the solutions produced by the allocation step. Results suggest that, in general, the Unified And-Or (UAO) operator based evaluation scheme performs significantly well compared to other evaluation approaches.

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