Research Publications Authored by SLIIT Staff

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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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Author: search.filters.author.Rankothge, WSubject: search.filters.subject.Optimization

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Now showing 1 - 4 of 4
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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.
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    PublicationEmbargo
    Towards a Smart City: Application of Optimization for a Smart Transportation Management System
    (IEEE, 2018-12) Thiranjaya, C; Rushan, R; Udayanga, P; Kaushalya, U; Rankothge, W
    Intelligent traffic planning, the efficiency of public transport and the improved connectivity of all road users in a city, comprise the mobility characteristics of a smart city. In the era of smart cities, efficient and well managed public transportation systems play a crucial role. The planning and allocation of public transportation systems, especially the public bus scheduling is one of the major resource allocation problems where the optimal resource allocation increases the passenger's as well as bus owner's satisfaction. In this research, we have proposed a platform for public transportation management, especially for optimal planning and scheduling of buses. We have used two approaches for our algorithms: Iterated Local Search (ILS) and Genetic Algorithm (GA). In this paper, we are presenting our optimization algorithms and their performances. Our results show that, using our algorithms, we can decide the optimal allocations of buses and plan the bus schedules dynamically in the order of seconds.
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    Sustainable tourism: Application of optimization algorithms to schedule tour plans
    (IEEE, 2019-01-31) Perera, D; Rathnayaka, C; Siriweera, L; Dilan, S; Rankothge, W
    One of the challenging problems in the tourism industry is to maintain the environmental sustainability of the tourists attracted locations while giving a better user experience for the tourists. The proposed platform for sustainable tourism management system consist with following modules: A prediction module to predict an approximate value on tourist arrival for each location, an optimization algorithm module to decide the number of tourists that can be accommodated in each location considering the environmental sustainability, and an optimal path generating module to show the best route to each location. The optimization algorithm module is developed to decide the number of tourists for each location based on two approaches: Genetic Algorithms and Iterated Local Search. Next the optimal path generating module is developed based on traveling salesman problem.In this paper, the performances of the optimization algorithm module and the optimal path generating module is presented. Results show that, using the suggestions given by the algorithms help the tourist to enjoy a better experience in travelling while ensuring the sustainability in the tourism industry.
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    Optimization of Customer-Friendly Manual Load Shedding System
    (IEEE, 2019-12-05) Fernando, W. D. I; Rankothge, W; Perera, A. D. S; Dissanayake, S. J; De Silva, W. D. S
    To maintain the supply and demand of electricity power, load-Shedding is one of the methods practiced by the energy suppliers to hold the power system balanced, when an energy deficit problem arises. Lacking a proper load shedding scheme will lead to system instability and it will cause serious system frequency decay. We have proposed a solution to optimize the manual load shedding schedule with the application of optimization techniques, specifically the Genetic Algorithms. We have considered current hold by all feeders throughout the country, and the time period of load shedding as main factors in the optimization model. Our results show that, using our proposed model, we can minimize the imbalance between the supply and demand of electricity by selecting the best feeder to be selected for load shedding under given constraints.