Abstract
This paper presents a new placement and routing method for layout generation of CMOS operational amplifiers (op-amps). Both circuit sizing and layout generation stages are performed automatically. In the proposed method, layout effects are considered during the layout generation. Layout parasitics and geometry information are extracted from a new automated layout generator. In this method, the multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used as an optimization algorithm. In order to verify the performance of the proposed method, the design of three-stage operational amplifier (op-amp) and two-stage class-AB operational trans-conductance amplifier (OTA) in a 0.18µm process CMOS technology with 1.8 V supply voltage are presented. The simulation results indicate the efficiency of the proposed analog layout generation method.
Highlights
Analog circuit design includes three main steps as follows [1], [2], [3], [4]: topology synthesis / selection, circuit sizing and layout design
This paper presents a new technique for placement and routing in analog layout generation using the multi-objective evolutionary algorithm based on decomposition (MOEA/D)
A multi-objective evolutionary algorithm based on decomposition (MOEA/D) has been proposed for multiobjective optimization problem (MOP) [35]
Summary
Analog circuit design includes three main steps as follows [1], [2], [3], [4]: topology synthesis / selection, circuit sizing and layout design. It is useful to perform circuit sizing and layout generation steps automatically. Parametric generators are used that code the whole layout of the circuit to increase execution speed Their definition is time-consuming and the solutions for devices’ sizes may differ from the ones intended in the definition step [21], [22], [23]. A placement and routing method for analog layout generation based on a modified cuckoo optimization algorithm (MCOA) is introduced in Ref [31] In this method, layout parasitics are considered to avoid performance deterioration. A multi-objective evolutionary algorithm based on decomposition (MOEA/D) has been proposed for multiobjective optimization problem (MOP) [35]. (2) is a Pareto optimal solution of the problem of Eq (1)
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