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    Efficient contrast enhancement of images using hybrid ant colony optimisation, genetic algorithm, and simulated annealing

    , Article Digital Signal Processing: A Review Journal ; Volume 23, Issue 3 , 2013 , Pages 879-893 ; 10512004 (ISSN) Hoseini, P ; Shayesteh, M. G ; Sharif University of Technology
    2013
    Abstract
    In this paper, we propose a hybrid algorithm including Genetic Algorithm (GA), Ant Colony Optimisation (ACO), and Simulated Annealing (SA) metaheuristics for increasing the contrast of images. In this way, contrast enhancement is obtained by global transformation of the input intensities. Ant colony optimisation is used to generate the transfer functions which map the input intensities to the output intensities. Simulated annealing as a local search method is utilised to modify the transfer functions generated by ant colony optimisation. And genetic algorithm has the responsibility of evolutionary process of antsE characteristics. The employed fitness function operates automatically and... 

    QSAR modelling of integrin antagonists using enhanced bayesian regularised genetic neural networks

    , Article SAR and QSAR in Environmental Research ; Volume 22, Issue 3-4 , May , 2011 , Pages 293-314 ; 1062936X (ISSN) Jalali Heravi, M ; Mani Varnosfaderani, A ; Sharif University of Technology
    2011
    Abstract
    Bayesian regularised genetic neural network (BRGNN) has been used for modelling the inhibition activity of 141 biphenylalanine derivatives as integrin antagonists. Three local pattern search (PS) methods, simulated annealing and threshold acceptance were combined with BRGNN in the form of a hybrid genetic algorithm (HGA). The results obtained revealed that PS is a suitable method for improving the ability of BRGNN to break out from the local minima. The proposed HGA technique is able to retrieve important variables from complex systems and nonlinear search spaces for optimisation. Two models with 8-3-1 artificial neural network (ANN) architectures were developed for describingα 4β 7 and α 4β... 

    Discrete harmony search algorithm for scheduling and rescheduling the reprocessing problems in remanufacturing: a case study

    , Article Engineering Optimization ; 2017 , Pages 1-17 ; 0305215X (ISSN) Gao, K ; Wang, L ; Luo, J ; Jiang, H ; Sadollah, A ; Pan, Q ; Sharif University of Technology
    Abstract
    In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and... 

    An exact algorithm for the minimum dilation triangulation problem

    , Article Journal of Global Optimization ; Volume 69, Issue 2 , 2017 , Pages 343-367 ; 09255001 (ISSN) Sattari, S ; Izadi, M ; Sharif University of Technology
    Abstract
    Given a triangulation of a point set on the plane, dilation of any pair of the points is the ratio of their shortest path length to their Euclidean distance. The maximum dilation over all pairs of points is called the dilation of this triangulation. Minimum dilation triangulation problem seeks a triangulation with the least possible dilation of an input point set. For this problem no polynomial time algorithm is known. We present an exact algorithm based on a branch and bound method for finding minimum dilation triangulations. This deterministic algorithm after generating an initial solution, iteratively computes a lower bound for the answer and then applies a branch and bound method to find... 

    Discrete harmony search algorithm for scheduling and rescheduling the reprocessing problems in remanufacturing: a case study

    , Article Engineering Optimization ; Volume 50, Issue 6 , 2018 , Pages 965-981 ; 0305215X (ISSN) Gao, K ; Wang, L ; Luo, J ; Jiang, H ; Sadollah, A ; Pan, Q ; Sharif University of Technology
    Taylor and Francis Ltd  2018
    Abstract
    In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and... 

    A modified PSO algorithm for minimizing the total costs of resources in MRCPSP

    , Article Mathematical Problems in Engineering ; Volume 2012 , 2012 ; 1024123X (ISSN) Khalilzadeh, M ; Kianfar, F ; Shirzadeh Chaleshtari, A ; Shadrokh, S ; Ranjbar, M ; Sharif University of Technology
    2012
    Abstract
    We introduce a multimode resource-constrained project scheduling problem with finish-to-start precedence relations among project activities, considering renewable and nonrenewable resource costs. We assume that renewable resources are rented and are not available in all periods of time of the project. In other words, there is a mandated ready date as well as a due date for each renewable resource type so that no resource is used before its ready date. However, the resources are permitted to be used after their due dates by paying penalty costs. The objective is to minimize the total costs of both renewable and nonrenewable resource usage. This problem is called multimode resource-constrained... 

    Hybrid ant colony optimization, genetic algorithm, and simulated annealing for image contrast enhancement

    , Article 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, 18 July 2010 through 23 July 2010, Barcelona ; 2010 ; 9781424469109 (ISBN) Hoseini, P ; Shayesteh, M. G ; Sharif University of Technology
    2010
    Abstract
    In this paper, we propose a hybrid algorithm including Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Simulated Annealing (SA) metaheuristics for increasing the contrast of images. In this way, the contrast enhancement is obtained by globally transformation of the input intensities. ACO is used to generate the transfer functions which map the input intensities to the output intensities. SA as a local search method is utilized to modify the transfer functions generated by ACO. GA has the responsibility of evolutionary process of ants' characteristics. The results indicate that the new method performs better than the previously presented methods from the subjective and objective...