Fuzzy genetic algorithm for floorplanning

Genetic algorithms (GAs) have been found to be very effective in solving numerous optimization problems, especially those with many (possibly) conflicting and noisy objectives. However, there seems to be no consensus as to what fitness measure to use in such situations, and how to rank individuals in a population on the basis of several conflicting objectives. Fuzzy logic provides an effective and easy way of dealing with such class of problems. In this work, we present a fuzzy genetic algorithm (FGA), which combines the parallel and robust search properties of GA with the expressive power of fuzzy logic. In the proposed FGA, the fitness of individuals is evaluated based on fuzzy logic rules expressed on linguistic variables modeling the desired objective criteria of the problem domain. Several fitness fuzzification approaches are evaluated and compared with Weighted Sum GA (WS-GA), where the fitness is set equal to a weighted sum of the objective criteria. Experimental evaluation was conducted using as a testbed the floorplanning of Very Large Scale Integrated (VLSI) circuits

Fuzzy genetic algorithm for floorplanning

Genetic algorithms (GAs) have been found to be very effective in solving numerous optimization problems, especially those with many (possibly) conflicting and noisy objectives. However, there seems to be no consensus as to what fitness measure to use in such situations, and how to rank individuals in a population on the basis of several conflicting objectives. Fuzzy logic provides an effective and easy way of dealing with such class of problems. In this work, we present a fuzzy genetic algorithm (FGA), which combines the parallel and robust search properties of GA with the expressive power of fuzzy logic. In the proposed FGA, the fitness of individuals is evaluated based on fuzzy logic rules expressed on linguistic variables modeling the desired objective criteria of the problem domain. Several fitness fuzzification approaches are evaluated and compared with Weighted Sum GA (WS-GA), where the fitness is set equal to a weighted sum of the objective criteria. Experimental evaluation was conducted using as a testbed the floorplanning of Very Large Scale Integrated (VLSI) circuits

Transaction-based Waveform Analysis for Functional Verification in IP Selection

Functional verification is an important aspect of IP selection. Formal verification and logic simulation are two traditional approaches for this problem. Both technqiues have substantial limiations. A methoddescribed in our work combines these two basic approach to achieve effective verification. A formal regular expression technique is merged with the simulation to provide meaningful transaction level verification of IP suitability. Implementation is illustrated by examples

Transaction-based Waveform Analysis for Functional Verification in IP Selection ABSTRACT

Functional verification is an important aspect of IP selection. Formal verification and logic simulation are two traditional approaches to this problem. Both techniques have substantial limitations. A method described in our work combines these two basic approaches to achieve effective verification. A formal regular expression technique is merged with the simulation to provide meaningful transaction level verification of IP suitability. Implementation is illustrated by examples

Timing Domain Algorithm for Nonlinear Optimization Problems in Interconnect Design

The necessity for computing robustly accurate sensitivities repeatedly for direct solution of nonlinear optimization problems and possibility of dealing with nonlinear circuit elements motivate a revisit of time domain methods. This paper illustrates the possibility of developing an efficient sysnthesis/analytical tool for high-speed interconnect networks by (a) employing a stable and fast time-domain numerical integration scheme to simulate the continuous approximation of the wave equation for transmission lines and to generate highly accurate sensitivities, and (b) using the integrator in multiple-shooting type signal-integrity-constrained non-linear optimizer to obtain values of the design parameters