A Development Framework for Rapid Metaheuristics Hybridization

While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to specific problems. For this reason, a software tool for rapid prototyping of algorithms would save considerable resources. This paper presents a generic software framework that reduces development time through abstract classes and software reuse, and more importantly, aids design with support of user-defined strategies and hybridization of meta-heuristics. Most interestingly, we propose a novel way of redefining hybridization with the use of the “request and response ” metaphor, which form an abstract concept for hybridization. Different hybridization schemes can now be formed with minimal coding, which gives our proposed Metaheuristics Development Framework its uniqueness. To illustrate the concept, we restrict to two popular metaheuristics Ants Colony Optimization and Tabu Search, and demonstrate MDF through the implementation of various hybridized models to solve the Traveling Salesman Problem. 1

Evaluation Of Noise In Dna Fingerprint Images Produced By

DNA fingerprint images produced by hybridization techniques are often degraded by different types of noise such as film grain noise and noise from electrophoresis, membrane, hybridization process, etc. The purpose of noise reduction is to obtain an image that differ as little as possible from the noise free image. The basic difficulty of the noise reduction technique is that, if applied indiscriminately, they tend to blur the image. Further, the effectiveness of each noise reduction technique tends to be affected by the type of noise to be filtered and the characteristics of the image to be processed. To perform an effective noise filtering, a noise model which describes the noise type is required. Methods such as SVD (Singular Value Decomposition) with power spectrum and local statistics (such as mean and variance) are applied to estimate the noise characteristics in hybridized DNA fingerprint images. The results obtained indicate that these type of images are affected by both additive and multiplicative noise. Homomorphic low pass filter and iterative KNN (K nearest neighbor) filter are applied to reduce the noise

Optimization Problems in Design of Oligonucleotides for

This research thesis was done under the supervision of Dr. Zohar Yakhini in th