On Optimizing BIST-Architecture by Using OBDD-based Approaches and Genetic Algorithms
نویسندگان
چکیده
We introduce a two-staged Genetic Algorithm for optimizing weighted random pattern testing in a Built-InSelf-Test (BIST) environment. The first stage includes the OBDD-based optimization of input probabilities with regard to the expected test length. The optimization itself is constrained to discrete weight values which can directly be integrated in a BIST environment. During the second stage, the hardware-design of the actual BIST-structure is optimized. Experimental results are given to demonstrate the quality of our approach.
منابع مشابه
Using and comparing metaheuristic algorithms for optimizing bidding strategy viewpoint of profit maximization of generators
With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous...
متن کاملOptimizing the AGC system of a three-unequal-area hydrothermal system based on evolutionary algorithms
This paper focuses on expanding and evaluating an automatic generation control (AGC) system of a hydrothermal system by modelling the appropriate generation rate constraints to operate practically in an economic manner. The hydro area is considered with an electric governor and the thermal area is modelled with a reheat turbine. Furthermore, the integral controllers and electri...
متن کاملOptimizing a multi-product closed-loop supply chain using NSGA-II, MOSA, and MOPSO meta-heuristic algorithms
This study aims to discuss the solution methodology for a closed-loop supply chain (CLSC) network that includes the collection of used products as well as distribution of the new products. This supply chain is presented on behalf of the problems that can be solved by the proposed meta-heuristic algorithms. A mathematical model is designed for a CLSC that involves three objective functions of ma...
متن کاملProposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms
In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...
متن کاملEfficient Genetic Based Methods for Optimizing the Reversible and Quantum Logic Circuits
Various synthesis methods have been proposed in the literature for reversible and quantum logic circuits. However, there are few algorithms to optimize an existing circuit with multiple constraints simultaneously. In this paper, some heuristics in genetic algorithms (GA) to optimize a given circuit in terms of quantum cost, number of gates, location of garbage outputs, and delay, are proposed. ...
متن کامل