Viral systems : a new bio-inspired optimisation approach

The paper presents a new approach to deal with combinatorial problems. It makes use of a biological analogy inspired by the performance of viruses. The replication mechanism, as well as the hosts’ infection processes is used to generate a metaheuristic that allows the obtention of valuable results. The viral system (VS) theoretical context is described and it is applied to a library of medium-to-large-sized cases of the Steiner problem for which the optimal solution is known. The method is compared with the metaheuristics that have provided the best results for the Steiner problem. The VS provides better solutions than genetic algorithms and certain tabu search approaches. For the most sophisticated tabu search approaches (the best metaheuristic approximations to the Steiner problem solution) VS provides solutions of similar quality

Viral system algorithm: foundations and comparison between selective and massive infections

This paper presents a guided and deep introduction to Viral Systems (VS), a novel bio-inspired methodology based on a natural biological process taking part when the organism has to give a response to an external infection. VS has proven to be very efficient when dealing with problems of high complexity. The paper discusses on the foundations of viral systems, presents the main pseudocodes that need to be implemented and illustrates the methodology application. A comparison between VS and other metaheuristics, as well between different VS approaches is presented. Finally trends and new research opportunities are presented for this bio-inspired methodology

A viral system algorithm to optimize the car dispatching in elevator group control systems of tall buildings

Nowadays is very common the presence of tall buildings in the business centres of the main cities of the world. Such buildings require the installation of numerous lifts that are coordinated and managed under a unique control system. Population working in the buildings follows a similar traffic pattern generating situations of traffic congestion. The problem arises when a passenger makes a hall call wishing to travel to another floor of the building. The dispatching of the most suitable car is the optimization problem we are tackling in this paper. We develop a viral system algorithm which is based on a bio-inspired virus infection analogy to deal with it. The viral system algorithm is compared to genetic algorithms, and tabu search approaches that have proven efficiency in the vertical transportation literature. The experiments undertaken in tall buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars, provide valuable results and show how viral system outperforms such soft computing algorithms.Plan Estatal de Investigación Científica y Técnica y de Innovación (España

Penerapan Algoritma Viral System Pada Single-Machine Total Weighted Tardiness Problem

Single Machine Total Weighted Tardiness Problem (SMTWTP) merupakan permasalahan klasik kombinatorial yang dikenal np-hard. Pada penelitian ini, suatu algoritma yang relatif baru yang terinspirasi dari sistem replikasi virus yang disebut sebagai Viral Systems digunakan untuk menyelesaikan permasalahan tersebut. Algoritma dengan proses pencarian terdiri dari Neighborhood dan mutasi tersebut memiliki delapan parameter. Penelitian ini menerapkan algoritma Viral Systems pada SMTWTP. Pengujian dilakukan untuk menganalisa parameter dan performansi algoritma dalam penyelesaian permasalahan. Hasil eksperimen menunjukkan bahwa setiap parameter memberikan pengaruh masing-masing terhadap algoritma dalam sisi hasil dan waktu komputasi. Eksperimen terhadap set data 40 pekerjaan, 50 pekerjaan, dan 100 pekerjaan menampilkan hasil bahwa algoritma dapat menyelesaikan 235 solusi optimal dari 275 permasalaha

2014 Annual Research Symposium Abstract Book

2014 annual volume of abstracts for science research projects conducted by students at Trinity College

DNA Sequencing

This book illustrates methods of DNA sequencing and its application in plant, animal and medical sciences. It has two distinct sections. The one includes 2 chapters devoted to the DNA sequencing methods and the second includes 6 chapters focusing on various applications of this technology. The content of the articles presented in the book is guided by the knowledge and experience of the contributing authors. This book is intended to serve as an important resource and review to the researchers in the field of DNA sequencing