International Journal of Innovative Computing and Applications 

About: International Journal of Innovative Computing and Applications is an academic journal published by Inderscience Publishers. The journal publishes majorly in the area(s): Computer science & Particle swarm optimization. It has an ISSN identifier of 1751-648X. Over the lifetime, 245 publications have been published receiving 1455 citations. The journal is also known as: IJICA.

A fuzzy adaptive turbulent particle swarm optimisation

Abstract: Particle Swarm Optimisation (PSO) algorithm is a stochastic search technique, which has exhibited good performance across a wide range of applications. However, very often for multimodal problems involving high dimensions, the algorithm tends to suffer from premature convergence. Analysis of the behaviour of the particle swarm model reveals that such premature convergence is mainly due to the decrease of velocity of particles in the search space that leads to a total implosion and ultimately fitness stagnation of the swarm. This paper introduces Turbulence in the Particle Swarm Optimisation (TPSO) algorithm to overcome the problem of stagnation. The algorithm uses a minimum velocity threshold to control the velocity of particles. The parameter, minimum velocity threshold of the particles is tuned adaptively by a fuzzy logic controller embedded in the TPSO algorithm, which is further called as Fuzzy Adaptive TPSO (FATPSO). We evaluated the performance of FATPSO and compared it with the Standard PSO (SPSO), Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison was performed on a suite of 10 widely used benchmark problems for 30 and 100 dimensions. Empirical results illustrate that the FATPSO could prevent premature convergence very effectively and it clearly outperforms SPSO and GA.

MALLBA: a software library to design efficient optimisation algorithms

Abstract: In this paper we discuss on the MALLBA framework, a software tool for the resolution of combinatorial optimisation problems using generic algorithmic skeletons implemented in C++. Every skeleton in the MALLBA library implements an optimisation method (exacts, metaheuristics and hybrids) and provides three different implementations for it: sequential, parallel for Local Area Networks and parallel for Wide Area Networks. This paper introduces some aspects about the software design of the MALLBA library, details of the most recent implemented skeletons and offers computational results for a scheduling problem to illustrate the utilisation of our library.

Analysis of exploration and exploitation in evolutionary algorithms by ancestry trees

Abstract: This paper introduces an ancestry tree-based approach for exploration and exploitation analysis. The approach introduces a data structure to record the evolution history of a population and a number of exploration and exploitation metrics. Such an approach not only provides insight of how and when the exploration and exploitation influence an evolution process, but also how the genetic structure of an individual is affected. It can be used to better understand inner working of an evolutionary algorithm or in evolutionary algorithm designing phase to develop suitable variation operators with good balance between exploration and exploitation. The approach is applied to the multi-objective 0/1 knapsack problem.

An evolvable hardware system in Xilinx Virtex II Pro FPGA

Abstract: In this paper, a new circuit architecture for image filter evolution is proposed. The evolvable system is based on the implementation of a search algorithm in the PowerPC processor which is available in Xilinx Virtex II Pro Field Programmable Gate Arrays (FPGAs). Candidate filters are evaluated in a domain-specific virtual reconfigurable circuit implemented using a reconfigurable logic of the same FPGA. As the PowerPC processor enables to execute more sophisticated search algorithms than an original solely circuit-based solution by Martinek and Sekanina, a higher performance can be obtained. In the FPGA, a resulting human-competitive filter can be evolved in 15 sec in average.

A two-tier scheme for greyscale quantum image watermarking and recovery

Abstract: A scheme is proposed to watermark and recover unmarked greyscale images on quantum computers. The hitherto inaccessible data from a quantum image-watermark pair is extracted from their classical conventional or non-quantum versions using which two quantum sub-circuits are used to execute the two-tier transformations comprising of changes that: 1 embed a visible and translucent watermark logo in a predetermined sub-area of the quantum replica of the cover image; 2 modify the remaining content of the cover image in a manner dictated by the watermark signal, so that the resulting distortions on the watermarked image are not easily discernible. Classical simulations of the image-watermark pairs and the various sub-circuits required to obtain the marked and unmarked images demonstrate the feasibility of the proposed scheme when the necessary quantum hardware are realised. The proposal advances available literature geared towards safeguarding quantum resources from unauthorised reproduction and confirmation of their proprietorship in cases of dispute thereby leading to commercial applications of quantum information.