—Genetic programming (GP), is a very general and efficient technique, often capable of outperforming more specialized techniques on a variety of tasks. In this paper, we suggest ...
In this paper we introduce an evolutionary algorithm for solving a copper mine planning problem. In the last 10 years this realworld problem has been tackled using linear integer p...
Abstract— This paper examines the performance characteristics of both asynchronous and synchronous parallel particle swarm optimisation algorithms in heterogeneous, fault-prone e...
Ian Scriven, David Ireland, Andrew Lewis, Sanaz Mo...
— Inspired from bacteria, a gene regulatory network model for signal transduction is presented in this paper. After describing experiments on stabilizing the population size for ...
Neale Samways, Yaochu Jin, Xin Yao, Bernhard Sendh...
—This paper presents an eavesdropper-proof algorithm that is capable of fast generating symmetric (secret) keys. Instead of literally exchanging secret keys, both the sender and ...
— The high-level synthesis process involves three interdependent and NP-complete optimization problems: (i) the operation scheduling, (ii) the resource allocation, and (iii) the ...
Christian Pilato, Daniele Loiacono, Fabrizio Ferra...
Abstract— This paper presents a genetic algorithmic approach for finding efficient paths in directed graphs when optimizing multiple objectives. Its aim is to provide solutions...
— Software evolution and update play a vital role in software engineering. It has many advantages, such as improving the efficiency of programming, reducing the cost of maintena...
— Many optimisation problems are multi-objective and change dynamically. Many methods use a weighted average approach to the multiple objectives. This paper introduces the usage ...