Forthcoming and Online First Articles

International Journal of Swarm Intelligence

International Journal of Swarm Intelligence (IJSI)

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International Journal of Swarm Intelligence (2 papers in press)

Regular Issues

  • A review of 0-1 knapsack problem by nature-inspired optimisation algorithms   Order a copy of this article
    by Ruchi Chauhan, Nirmala Sharma, Harish Sharma 
    Abstract: Nature is the origin of all the knowledge. Researches have built nature-inspired optimisation (NIO) algorithms, that follow natural principles to find solutions, for the real life problems. In the binary knapsack problem (0/1KP), a bag (or a knapsack) has to be filled with articles, where each article has a weight and a profit value, the articles are filled in the knapsack, in whole numbers, up to a weight limit, to attain the optimum profit. The 0/1KP does the optimum sub-structure selection from a given set of articles, i.e., there can be different optimum solutions for a given 0/1KP. The aim of this research is to discuss the NIO algorithms innovated for solving the 0/1KP. The review creates foundation, for future research on optimising the 0/1KP, from meta-heuristic NIO techniques.
    Keywords: nature-inspired optimisation; NIO; 0-1 knapsack problem; 0/1KP; NP-hard problems; swarm intelligence.
    DOI: 10.1504/IJSI.2022.10051132
  • Retrospection and investigation of ANN-based MPPT technique in comparison with soft computing-based MPPT techniques for PV solar and wind energy generation system   Order a copy of this article
    by Sunita Chahar, Dinesh Kumar Yadav 
    Abstract: This article discusses the previously available research and summarises the state of knowledge of soft computing artificial neural network (ANN)-based control techniques for renewable energy systems. In recent years, wind and photovoltaic (PV) solar energy systems have been developed as key renewable energy sources. The main issue is to operate these energy sources for maximum power output in abrupt changes in environmental conditions. Besides different types of conventional control techniques, the soft computing-based control system has proved efficient in extracting the highest available output. There are few articles are available in the literature on ANN-based control systems in wind energy systems, however, sufficient research has been carried out for the ANN-based maximum power extraction techniques for PV solar. This article highlights the important features such as better controllability and performance of ANN-based control techniques in comparison with the other types of soft computing-based-tactics for PV solar and wind energy systems.
    Keywords: traditional algorithm; novel algorithm; hybrid algorithm; artificial neural network; ANN; solar photovoltaic; wind; renewable; maximum power point tracking.
    DOI: 10.1504/IJSI.2023.10055513