Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength ...

The process of cloning variants of a system to accommodate increasing customization is often state of the practice where code duplication is caused by the combination of maintenance problems, high customization, and time pressure. This particular situation motivates the research on similarity analysis of system variants. Similarity determination, variability information recovery, and evolution ...

The performance of any algorithm will largely depend on the setting of its algorithmdependent parameters. The optimal setting should allow the algorithm to achieve the best performance for solving a range of optimization problems. However, such parameter tuning is itself a tough optimization problem. In this chapter, we present a framework for self-tuning algorithms so that an algorithm to be t...

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Measurement of solar radiance demands expensive devices to be used. Alternatively, estimator models are used instead. In this paper, a new method based on the empirical equations is introduced to estimate the monthly average daily global solar radiation on a horizontal surface. The proposed method uses Intelligent Water ...

The use of meta-heuristic optimization methods have become quite generic in the past two decades. This paper provides a theoretical investigation to find optimum design parameters of the Stirling heat engines using a recently presented nature-inspired method namely the gray wolf optimization (GWO). This algorithm is utilized for the maximization of the output power/thermal efficiency as well as...

This work details early research aimed at applying the powerful resource allocation mechanism deployed in Stochastic Diffusion Search (SDS) to the Differential Evolution (DE), effectively merging a nature inspired swarm intelligence algorithm with a biologically inspired evolutionary algorithm. The results reported herein suggest that the hybrid algorithm, exploiting information sharing between...

This paper motivates research into implementing nature-inspired algorithms in decentralised, asynchronous and parallel environments. These characteristics typify environments such as Peer-To-Peer systems, the Grid and autonomic computing which demand robustness, decentralisation, parallelism, asynchronicity and self-organisation. Nature-inspired systems promise these properties. However, curren...