This paper describes a new parallel algorithm for solving the m-machines, n-jobs flow-shop scheduling problem as well as its implementation on a distributed memory multiprocessor. The algorithm is basically a parallel...
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This paper describes a new parallel algorithm for solving the m-machines, n-jobs flow-shop scheduling problem as well as its implementation on a distributed memory multiprocessor. The algorithm is basically a parallelization of the usual branch-and-bound method. It also takes advantage of the all-search method to keep the efficiency of parallel processing reasonably high when subproblems become smaller than a certain size. The performance evaluation is done by comparing the parallel execution of this algorithm on the nCUBE2 multiprocessor and the sequential execution of the branch-and-bound with depth-first search algorithm. The result shows that the mean speedup ratio for some conditions of the problem is more than the number of processors, and the mean speedup ratio for the conditions on which the sequential executions complete quickly is not smaller than 1.
This article considers the concept of a linear separation direct algorithm introduced by V.A. Bondarenko in 1983. The concept of a direct algorithm is defined using the solution graph of a combinatorial optimization p...
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This article considers the concept of a linear separation direct algorithm introduced by V.A. Bondarenko in 1983. The concept of a direct algorithm is defined using the solution graph of a combinatorial optimization problem. The vertices of this graph are all feasible solutions of the problem. Two solutions are called adjacent if there are input data for which these and only these solutions are optimal. A key feature of direct algorithms is that their complexity is bounded from below by the clique number of the solution graph. In 2015-2018, there were five articles published, the main results of which are estimates of the clique numbers of polyhedron graphs associated with various combinatorial optimization problems. The thesis that the class of direct algorithms is broad and includes many classical combinatorial algorithms, including the branch-and-bound algorithm for the traveling salesman problem proposed by J.D.C. Little, K.G. Murty, D.W. Sweeney, and C. Karel in 1963, was the main motivation for these articles. We show that this algorithm is not a direct algorithm. Earlier, in 2014, the author of this article showed that the Hungarian algorithm for the assignment problem is not a direct algorithm. Therefore, the class of direct algorithms is not as broad as previously assumed.
Current methods of general 0-1 fractional programming (G-FP) can only find the local optimum. This paper proposes a new method of solving G-FP problems by a mixed 0-1 linear program to obtain a global optimum. Given a...
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Current methods of general 0-1 fractional programming (G-FP) can only find the local optimum. This paper proposes a new method of solving G-FP problems by a mixed 0-1 linear program to obtain a global optimum. Given a mixed 0-1 polynomial term xy where x is a 0-1 variable and 0 < y less-than-or-equal-to 1, we develop a theorem to transfer the xy term into a set of mixed 0-1 linear inequalities. Based on this theorem, a G-FP problem can be solved by a branch-and-bound method to obtain the global solution.
We consider in this article a factor model in portfolio selection with roundlot constraints. Mathematically, this model leads to a quadratic integer programming problem. We exploit the separable structure of the model...
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We consider in this article a factor model in portfolio selection with roundlot constraints. Mathematically, this model leads to a quadratic integer programming problem. We exploit the separable structure of the model in order to derive Lagrangian bounds. A branch-and-bound algorithm based on Lagrangian relaxation and continuous relaxation is then developed for solving this model. Computational results are reported for test problems with up to 150 securities.
In an assembly line of a just-in-time (JIT) production system, workers have the power and the responsibility to stop the line when they fail to complete their operations within their work zones. This paper deals with ...
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In an assembly line of a just-in-time (JIT) production system, workers have the power and the responsibility to stop the line when they fail to complete their operations within their work zones. This paper deals with a sequencing problem for the mixed-model assembly conveyor line in the JIT production system. In some environment, the most important criterion is the line stoppage rather than the variation of production rates. The problem is to find an optimal sequence of units that minimizes the total line stoppage time. Lower and upper bounds of the total line stoppage time are derived and the branch-and-bound method is applied to the problem, A numerical example is given.
In considering the problem of sequentially ordering N jobs, it is known that large-scale problems cannot be solved readily in order to find optimality since there are N! possibilities to the schedules. In this paper, ...
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In considering the problem of sequentially ordering N jobs, it is known that large-scale problems cannot be solved readily in order to find optimality since there are N! possibilities to the schedules. In this paper, a quick optimal algorithm for sequencing jobs processed on one machine to minimize total tardiness is proposed. The optimal algorithm relies upon the branch-and-bound method applied directly to Lawler's decomposition theorem and gives an optimal solution. In the algorithm, special care is given to the calculation procedure and the setup of the upper bound values to shorten the calculation time. (C) 1999 Elsevier Science B.V. All rights reserved.
A unified feature extraction scheme, the two-dimensional (2-D) linear prediction model-based decorrelation method, is presented. By applying 2-D causal linear prediction model to decorrelate a textured image, the very...
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A unified feature extraction scheme, the two-dimensional (2-D) linear prediction model-based decorrelation method, is presented. By applying 2-D causal linear prediction model to decorrelate a textured image, the very heavy computation load required when using a whitening operator to decorrelate the image, or the significant information loss when using the gradient operator to approximately whiten the image is avoided. The texture model-based decorrelation provides three sets of features to perform texture classification: the coefficients of the 2-D linear prediction, the moments of error residuals and the autocorrelation values. An optimum feature-selection scheme using modified branch-and-bound method was introduced to reduce information redundancy. After feature selection, 100% classification accuracy was achieved for a 20-class texture problem. Experiments show that this feature extraction scheme is truly information lossless, effective, and fast.","doi":"10.1109/34.24801","publicationTitle":"IEEE Transactions on Pattern Analysis and Machine Intelligence","startPage":"661","endPage":"665","rightsLink":"http://***/AppDispatchServlet?publisherName=ieee&publication=0162-8828&title=Two-dimensional+linear+prediction+model-based+decorrelation+method&isbn=&publicationDate=June+1989&author=Z.+Lin&ContentID=10.1109/34.24801&orderBeanReset=true&startPage=661&endPage=665&volumeNum=11&issueNum=6","displayPublicationTitle":"IEEE Transactions on Pattern Analysis and Machine Intelligence","pdfPath":"/iel1/34/938/***","keywords":[{"type":"IEEE Keywords","kwd":["Predictive models","Decorrelation","Feature extraction","Image texture analysis","Image analysis","Two dimensional displays","Autocorrelation","Image segmentation","Parametric statistics","Correlation"]},{"type":"INSPEC: Controlled Indexing","kwd":["picture processing","correlation methods","filtering and prediction theory","pattern recognition"]},{"type":"INSPEC: Non-Controlled Indexing","kwd":["
We formulate the minimum spanning tree problem with resource allocation (MSTRA) in two ways, as discrete and continuous optimization problems (d-MSTRA/c-MSTRA), prove these to be NP-hard, and present algorithms to sol...
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We formulate the minimum spanning tree problem with resource allocation (MSTRA) in two ways, as discrete and continuous optimization problems (d-MSTRA/c-MSTRA), prove these to be NP-hard, and present algorithms to solve these problems to optimality. We reformulate d-MSTRA as the knapsack constrained minimum spanning tree problem, and solve this problem using a previously published branch-and-bound algorithm. By applying a 'peg test', the size of d-MSTRA is (significantly) reduced. To solve c-MSTRA, we introduce the concept of f-fractional solution, and prove that an optimal solution can be found within this class of solutions. Based on this fact, as well as conditions for 'pruning' subproblems, we develop an enumerative algorithm to solve c-MSTRA to optimality. We implement these algorithms in ANSI C programming language and, through extensive numerical tests, evaluate the performance of the developed codes on various types of instances. (C) 2016 The Authors. Published by Elsevier Ltd.
A new pruning method for interval branch and bound algorithms is presented. In reliable global optimization methods there are several approaches to make the algorithms faster. In minimization problems, interval B&...
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A new pruning method for interval branch and bound algorithms is presented. In reliable global optimization methods there are several approaches to make the algorithms faster. In minimization problems, interval B&B methods use a good upper bound of the function at the global minimum and good lower bounds of the function at the subproblems to discard most of them, but they need efficient pruning methods to discard regions of the subproblems that do not contain global minimizer points. The new pruning method presented here is based on the application of derivative information from the Baumann point. Numerical results were obtained by incorporating this new technique into a basic Interval B&B Algorithm in order to evaluate the achieved improvements.
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