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Hasani K.,Islamic Azad University | Kravchenko S.A.,United Institute of Informatics Problems | Werner F.,Otto Von Guericke University of Magdeburg
International Journal of Production Research | Year: 2014

This paper considers the problem of scheduling a set of jobs on two parallel machines to minimise the makespan. Each job requires a set-up which must be done by a single server. The objective is to minimise the makespan. For this strongly NP-hard problem, a simulated annealing and a genetic algorithm are presented. The performance of these algorithms is evaluated for instances with up to 1000 jobs. The results are compared with existing algorithms from the literature. It is observed that the algorithms presented in this paper both show an excellent behaviour and that the objective function values obtained are very close to a lower bound. The superiority over existing algorithms is obtained by using a composite neighbourhood (mutation), generating several neighbours from sub-neighbourhoods with different probabilities and taking the best solution as generated neighbour. © 2014 Taylor & Francis. Source


Gholami O.,Islamic Azad University | Sotskov Y.N.,United Institute of Informatics Problems
International Journal of Advanced Manufacturing Technology | Year: 2014

We consider a multistage processing system, which includes both identical (parallel) machines that can process the same set of operations and different machines that can process only different operation sets. A release time ri is given for each job Ji to be processed. For such a processing system, we minimize the makespan, i.e., problem IJ|ri |Cmax is considered. The problem IJ|ri |Cmax is an extension of the classical job-shop problem J |ri |Cmax for the case when parallel (or identical)machines are also given. Both problems J |ri |Cmax and IJ|ri |Cmax are strongly NPhard. A mixed graph model used for solving the problem J |ri |Cmax is generalized for the problem IJ|ri |Cmax. Using the mixed graph model, we developed a fast heuristic algorithm for solving the problem IJ|ri |Cmax. Computational experiments were conducted to evaluate the performance of the algorithm on the 22 benchmark instances and on the 40 new randomly generated instances of the problem IJ||Cmax. For the small and moderate instances, the exact values of the objective function were compared with those calculated by the proposed heuristic algorithm. The average relative error was not greater than 2.4 % for all instances with available optimal schedules. Computational results showed that the developed algorithm runs faster than some other heuristics being tested, and the schedules constructed by the developed algorithm have smaller makespans. © Springer-Verlag London 2013. Source


Barketau M.,United Institute of Informatics Problems | Pesch E.,University of Siegen
International Journal of Production Research | Year: 2015

We consider the following optimisation problem that we encountered during the consolidation process of trains in a container transhipment terminal as well as in the intermediate storage of containers in sea ports in order to accelerate the loading and unloading of the vessels. There are n ordered pairs of points in the m-dimensional metric space: (Formula presented.). The problem is to find a permutation (Formula presented.) of numbers (Formula presented.) minimising the function (Formula presented.) where (Formula presented.) is the metric of the space. The problem can be considered as a special case of the asymmetric travelling salesman problem. As for Euclidean, Manhattan and Chebyshev metric the problem is NP-hard (as a generalisation of the well-known TSP problem) we propose the simple approximation algorithm with the approximation guarantee equal to 3. The approximation guarantee is tight as will be shown by a sequence of instances for which the approximation ratio converges to 3. © 2015 Taylor & Francis Source


Novoselova N.,United Institute of Informatics Problems
Intelligent Data Analysis | Year: 2014

The stability techniques widely used in bioinformatics research estimate clusterings with a pre-defined number of clusters. But the complex nature of bio-molecular data necessitates the extension of the stability techniques in order to validate the whole clusters' hierarchy without strict setting of the number of clusters beforehand. In this paper we proposed a stability-based algorithm HClusterV to estimate the individual clusters of the dendrogram. It is based on a repetitive construction of the hierarchy of clusters followed by the calculation of the original consensus matrix. The proposed algorithm allows to overcome the deficiency of the previous approach and to improve the reliability of the stability indices. Experiments on two simulated datasets and further comparative analysis confirmed the advantages of our approach. The proposed HClusterV algorithm was evaluated on two real microarray datasets and gave the results consistent with the corresponding non-hierarchical stability-based methods and relevant biological knowledge. © 2014 - IOS Press and the authors. All rights reserved. Source


Kravchenko S.A.,United Institute of Informatics Problems | Werner F.,Otto Von Guericke University of Magdeburg
Journal of Scheduling | Year: 2011

The basic scheduling problem we are dealing with is the following. There are n jobs, each requiring an identical execution time. All jobs have to be processed on a set of parallel machines. Preemptions can be either allowed or forbidden. The aim is to construct a feasible schedule such that a given criterion is minimized. In this paper, we survey existing approaches for the problem class considered. © Springer Science+Business Media, LLC 2011. Source

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