The conventional Butterfly Optimization Algorithm (BOA) does not appropriately balance the explor... more The conventional Butterfly Optimization Algorithm (BOA) does not appropriately balance the exploration and exploitation characteristics of an algorithm to solve present-day challenging optimization problems. For the same, in this paper, a novel hybrid BOA (MPBOA, in short) is suggested, where the BOA is combined with mutualism and parasitism phases of the Symbiosis Organisms Search (SOS) algorithm to enhance the search behaviour (both global and local) of BOA. The mutualism phase is applied with the global phase of BOA, and the parasitism phase is added with the local phase of BOA to ensure a better trade-off between the global and local search of the proposed algorithm. A suit of twenty-five benchmark functions is employed to investigate its performance with several other state-of-the-art algorithms available in the literature. Also, to check its performance statistically, the Friedman rank test and t-test are carried out. The consistency of the proposed algorithm is tested with a boxplot diagram. Also, four real-world problems are solved to check the efficiency of the algorithm in solving industrial problems. Finally, the proposed MPBOA is utilized to obtain the optimal threshold in the multilevel thresholding problem of the segmentation of individual images. From the obtained results, it is found that the overall performance of the newly introduced MPBOA is satisfactory in terms of its search behaviour and convergence time to obtain global optima.
The uncontrolled extraction followed by technological advancements and increasing population has ... more The uncontrolled extraction followed by technological advancements and increasing population has induced an increase in Green House Gas concentration in the atmosphere and the outcome was global warming followed by the change in climatic pattern in different places of the world has reduced per capita availability of water. Due to climate change, water accessibility for manufacturing also gets affected. The volume of water which is also avowed as virtual water is significantly impacting the industrial output. Few studies tried to estimate the consequences of variation in climatic conditions change on virtual water utilization but at present, no study has considered the same impact on the availability of virtual water. That is why climate change impact was estimated on the availability of virtual water per consumer of the industrial output of the region in the current study. The estimation was depicted in cardinal rather than ordinal output. Also, the Polynomial Neural Network architecture-based Group Method of Data Handling was utilized as the optimal classifier of climate change impact on virtual water availability per consumer. Four metro cities of the Indian Sub-continent were considered as the study area. According to the results New Delhi is worst and Kolkata least affected for the Intergovernmental Panel on Change of Climate proposed B2 scenario. In the case of the A2 scenario, here also New Delhi was found to be the worst affected and Mumbai least affected. The classifier was found to be more efficient than Stepwise
The conventional Butterfly Optimization Algorithm (BOA) does not appropriately balance the explor... more The conventional Butterfly Optimization Algorithm (BOA) does not appropriately balance the exploration and exploitation characteristics of an algorithm to solve present-day challenging optimization problems. For the same, in this paper, a novel hybrid BOA (MPBOA, in short) is suggested, where the BOA is combined with mutualism and parasitism phases of the Symbiosis Organisms Search (SOS) algorithm to enhance the search behaviour (both global and local) of BOA. The mutualism phase is applied with the global phase of BOA, and the parasitism phase is added with the local phase of BOA to ensure a better trade-off between the global and local search of the proposed algorithm. A suit of twenty-five benchmark functions is employed to investigate its performance with several other state-of-the-art algorithms available in the literature. Also, to check its performance statistically, the Friedman rank test and t-test are carried out. The consistency of the proposed algorithm is tested with a boxplot diagram. Also, four real-world problems are solved to check the efficiency of the algorithm in solving industrial problems. Finally, the proposed MPBOA is utilized to obtain the optimal threshold in the multilevel thresholding problem of the segmentation of individual images. From the obtained results, it is found that the overall performance of the newly introduced MPBOA is satisfactory in terms of its search behaviour and convergence time to obtain global optima.
The uncontrolled extraction followed by technological advancements and increasing population has ... more The uncontrolled extraction followed by technological advancements and increasing population has induced an increase in Green House Gas concentration in the atmosphere and the outcome was global warming followed by the change in climatic pattern in different places of the world has reduced per capita availability of water. Due to climate change, water accessibility for manufacturing also gets affected. The volume of water which is also avowed as virtual water is significantly impacting the industrial output. Few studies tried to estimate the consequences of variation in climatic conditions change on virtual water utilization but at present, no study has considered the same impact on the availability of virtual water. That is why climate change impact was estimated on the availability of virtual water per consumer of the industrial output of the region in the current study. The estimation was depicted in cardinal rather than ordinal output. Also, the Polynomial Neural Network architecture-based Group Method of Data Handling was utilized as the optimal classifier of climate change impact on virtual water availability per consumer. Four metro cities of the Indian Sub-continent were considered as the study area. According to the results New Delhi is worst and Kolkata least affected for the Intergovernmental Panel on Change of Climate proposed B2 scenario. In the case of the A2 scenario, here also New Delhi was found to be the worst affected and Mumbai least affected. The classifier was found to be more efficient than Stepwise
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Papers by Apu Saha