Research Publications Authored by SLIIT Staff

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4195

This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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2018 - 201912020 - 20231

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Subject: search.filters.subject.genetic algorithm

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    PublicationOpen Access
    Optimization of VISSIM Driver Behavior Parameter Values Using Genetic Algorithm
    (Creative Commons Attribution, 2023-02-13) Gunarathne, D; Amarasingha, N; Kulathunga, A; Wicramasighe, V
    Modeling effective vehicular traffic is a highly contested topic, especially in developing countries like Sri Lanka, which has a wide range of driving conditions. VISSIM microsimulation software is currently used by Road Development Authority (RDA) and relevant authorities to perform traffic management solutions in Sri Lanka. However, it is required to do modifications to the existing driver behavior parameter values to effectively reflect the realistic traffic conditions observed in the real-world in the simulated model. The main purpose of this study is to calibrate the VISSIM driver behavior parameter values using a genetic algorithm (GA). The methodology and results of the VISSIM model’s sensitivity analysis and calibration, which was developed for the Malabe three-legged signalized intersection, are presented in this study. A sensitivity analysis was used to find the most sensitive driver behavior parameters. Using the multi-objective GA optimization tool in the MATLAB software's optimization toolbox, the optimum driver behavior parameter values for these identified most sensitive driver behavior parameters were determined. The findings revealed that GA optimization is effective in reducing the difference between observed and simulated results.
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    PublicationOpen Access
    Experimental study on an efficient dengue disease management system: Planning and optimizing hospital staff allocation
    (The Science and Information (SAI) Organization, 2018-01) Jayasuriya, M. M. C; Galappaththi, G. K. K. T; Sampath, M. A. D; Nipunika, H. N; Rankothge, W
    Dengue has become a serious health hazard in Sri Lanka with the increasing cases and loss of human lives. It is necessary to develop an efficient dengue disease management system which could predict the dengue outbreaks, plan the countermeasures accordingly and allocate resources for the countermeasures. We have proposed a platform for Dengue disease management with following modules: (1) a prediction module to predict the dengue outbreak and (2) an optimization algorithm module to optimize hospital staff according to the predictions made on future dengue patient counts. This paper focuses on the optimization algorithm module. It has been developed based on two approaches: (1) Genetic Algorithm (GA) and (2) Iterated Local Search (ILS). We are presenting the performances of our optimization algorithm module with a comparison of the two approaches. Our results show that the GA approach is much more efficient and faster than the ILS approach.