Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Subject: search.filters.subject.Multi-objective optimization

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    Multi-objective Genetic Algorithm for efficient point matching in multi-sensor satellite image
    (2012) Senthilnath, J.; Omkar, S.N.; Mani, V.; Kalro, N.P.; Diwakar, P.G.
    This paper investigates a new approach for point matching in multi-sensor satellite images. The feature points are matched using multi-objective optimization (angle criterion and distance condition) based on Genetic Algorithm (GA). This optimization process is more efficient as it considers both the angle criterion and distance condition to incorporate multi-objective switching in the fitness function. This optimization process helps in matching three corresponding corner points detected in the reference and sensed image and thereby using the affine transformation, the sensed image is aligned with the reference image. From the results obtained, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient. © 2012 IEEE.
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    A hybrid discrete firefly algorithm for multi-objective flexible job shop scheduling problems with maintenance activity
    (Trans Tech Publications Ltd ttp@transtec.ch, 2014) Karthikeyan, S.; Asokan, P.; Chandrasekaran, M.
    This paper presents a novel hybrid discrete firefly algorithm (HDFA) for solving the multi-objective flexible job shop scheduling problem with non fixed availability constraints (FJSP - nfa) due to maintenance activity. Three minimization objectives-the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. In this study, the discrete firefly algorithm is adopted to solve the problem, in which the machine assignment and operation sequence are processed by constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In addition the decoding mechanism considering the maintenance activity is presented. A neighbourhood based local search is hybridized to enhance the exploitation capability. Representative benchmark problems are solved in order to evaluate and study the performance of the proposed algorithm. © (2014) Trans Tech Publications, Switzerland.
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    Multi-objective optimization of various type finned heat sink with phase change materials (PCM)
    (Institute of Physics, 2022) Muthamil Selvan, N.; Trilok, G.; Gnanasekaran, N.
    The paper focuses on optimizing hybrid PCM filled heat sinks with a multi-objective approach. In the current study, the fins are oriented both horizontally at the sidewalls and vertically at the bottom side in the enclosure. Two heat sinks with different types of fin shapes are introduced in the enclosure. A rectangular shape finned heat sink, and a tapered shape finned heat sink is incorporated in both sidewalls and bottom walls. The study's main goal is to optimize the PCM-based heat sink to prolong the charging cycle (melting) and shorten the discharging cycle (solidification). The PCM used in the study is n-eicosane, and the material for the heat sink is aluminum. A heat flux with constant supply of 2000 W/m2 is provided at the enclosure bottom, and the remaining walls are insulated. A 2-D numerical simulation is done using the commercial software ANSYS Fluent. The multi-objective optimization is carried out using the technique for order preference by similarity to ideal solution (TOPSIS) optimization technique. For a constant PCM volume for both the cases, fin spacing, fin positioning, and fin heights are varied. The output results determined the optimum configuration for the stretched melting period and minimized solidification period. © Published under licence by IOP Publishing Ltd.