This research paper deals with process optimization via linear programming application. It presents the results of a survey conducted on a sample set consisting of industrial plants operating both in the Slovak republ...
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ISBN:
(纸本)9781315673790;9781138028562
This research paper deals with process optimization via linear programming application. It presents the results of a survey conducted on a sample set consisting of industrial plants operating both in the Slovak republic and abroad. The scientific aims of this research paper is to explore the possibilities of linear programming utilization in process optimization among Slovak and foreign industrial plants and to create foundations for a model of process optimization in selected production company using linear programming methods. The object of this research is the selected production processes and the research subject of this paper is linear programming methods. We tested three related hypotheses in this paper with the most significant benefit being the creation of an image of recent linear programming applications in practice by Slovak industrial plants, mapping its economic benefits, and proposing requirements for a model of process optimization based on a linear programming foundation.
It is well known that linear programming is P-complete, with a logspace reduction. In this work we ask whether linear programming remains P-complete, even if the polyhedron (i.e., the set of linear inequality constrai...
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ISBN:
(纸本)9781450340571
It is well known that linear programming is P-complete, with a logspace reduction. In this work we ask whether linear programming remains P-complete, even if the polyhedron (i.e., the set of linear inequality constraints) is a fixed polyhedron, for each input size, and only the objective function is given as *** formally, we consider the following problem: maximize cx, subject to Ax <= b;x is an element of R-d, where A,b are fixed in advance and only c is given as an input. We start by showing that the problem remains P-complete with a logspace reduction, thus showing that n(o(1))-space algorithms are unlikely. This result is proved by a direct classical reduction. We then turn to study approximation algorithms and ask what is the best approximation factor that could be obtained by a small space algorithm. Since approximation factors are mostly meaningful when the objective function is non-negative, we restrict ourselves to the case where x >= 0 and c >= *** show that (even in this possibly easier case) approximating the value of max c.x (within any polynomial factor) is P-complete with a polylog space reduction, thus showing that 2((log n)o(1)) -space approximation algorithms are unlikely. The last result is proved using a recent work of Kalai, Raz, and Rothblum, showing that every language in P has a no-signaling multi-prover interactive proof with poly-logarithmic communication complexity. To the best of our knowledge, our result gives the first space hardness of approximation result proved by a PCP-based argument
A procedure which may be used to estimate the fire resistance of a steel sway frame load-bearing structure, based on the linear programming method, is presented and discussed in this paper. The approach to the general...
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ISBN:
(纸本)9781315623191;9781138029460
A procedure which may be used to estimate the fire resistance of a steel sway frame load-bearing structure, based on the linear programming method, is presented and discussed in this paper. The approach to the general problem formulation is shown in detail, including the specification of the objective function as well as the basic rules governing the development of the authoritative constraints. Interaction of bending moment and axial force is also taken into account in the recommended computational algorithm. The critical temperature, determined for the whole frame and associated with the occurrence of such potentially possible purely plastic failure mode which corresponds to the lowest activation temperature, constitutes the sought resistance measure.
Minimization of voltage deviations and power loss can be controlled by optimal reactive power dispatch for voltage stability of the system. This paper presents Genetic Algorithm approach for system parameters enhancem...
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ISBN:
(纸本)9781467399395
Minimization of voltage deviations and power loss can be controlled by optimal reactive power dispatch for voltage stability of the system. This paper presents Genetic Algorithm approach for system parameters enhancement and optimal reactive power dispatch. The transformers tap changers, generator exciters, switchable VAR sources are used as control variables for improvement of system parameters. The proposed methodology is based on the minimization of voltage deviations at load buses. The suggested approach permits the optimization variables to be presented in their natural form in the genetic population. For effective processing of Genetic Algorithm (GA), scattered crossover, constraint dependent mutation and double vector population operator which can directly deal with the floating point numbers are considered. The developed GA is tested on a few simulated practical Indian 24 bus system. The performance of GA is compared with conventional linear programming (LP) method and results are presented for illustration purpose. The correctiveness of voltage stability is measured in terms of system parameters.
New technologies allow to carry out a change in the way we educate more focused on the student rather than the teacher. In this regard, with the support of Information and Communications Technology (TIC) is very commo...
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ISBN:
(纸本)9781509061495
New technologies allow to carry out a change in the way we educate more focused on the student rather than the teacher. In this regard, with the support of Information and Communications Technology (TIC) is very common nowadays, students are increasingly using their mobile devices in the classroom, becoming the best friend student, figuratively. Based on the above drawing these guidelines, this paper presents the development of an App for calculating basic feasible solutions to transport problems to support the teaching-learning process to be used inside and outside the classroom;this app is to provide a learning environment movement to transport problems in linear programming (PL).
In this work, we consider adaptive linear programming (LP) decoding of linear codes over GF(8). In particular, we give explicit constructions of valid inequalities (using no auxiliary variables) for the codeword polyt...
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ISBN:
(纸本)9781509025299
In this work, we consider adaptive linear programming (LP) decoding of linear codes over GF(8). In particular, we give explicit constructions of valid inequalities (using no auxiliary variables) for the codeword polytope (or the convex hull) of the so-called constant-weight embedding of a single parity-check code over GF(8) that all are facet-defining. We conjecture that these inequalities together with so-called simplex constraints give a complete and irredundant description of the embedded (under the constant-weight embedding) codeword polytope. Furthermore, these sets of inequalities are used to develop an efficient (as compared to a static approach) exact (assuming that the conjecture is true) adaptive LP decoder for linear codes over GF(8). Numerical results show that only a very small subset of these inequalities is necessary for achieving close-to-exact LP decoding performance.
Cloud computing plays a vital role in today's IT industry, as it offers tremendous computing and storage facilities for the tasks and outsourced data respectively. The major security concern during the computation...
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ISBN:
(纸本)9781509013388
Cloud computing plays a vital role in today's IT industry, as it offers tremendous computing and storage facilities for the tasks and outsourced data respectively. The major security concern during the computations is to protect customer's confidential data. The mechanism of this paper decomposes widely applicable linear programming (LP) computation outsourcing into public LP solvers running on a cloud. Efficient privacy preserving problem transformation techniques allows customers to transform original LP into some random LP by keeping private LP parameters and protect input output information. This paper gives detailed mathematical analysis for original LP transformations and LP problem solving. It also proposes a method of adding a fake variable into linear program which will be transformed to random one so that it will be more difficult for an attacker to guess the original problem. The results obtained from the experimentation prove to be efficient and incurs close to zero additional cost.
This paper deals with the problem of stability and stabilization of Takagi-Sugeno (T-S) fuzzy systems with a fixed delay by linear programming (LP) while imposing positivity in closed-loop. The sufficient conditions o...
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ISBN:
(纸本)9781467389532
This paper deals with the problem of stability and stabilization of Takagi-Sugeno (T-S) fuzzy systems with a fixed delay by linear programming (LP) while imposing positivity in closed-loop. The sufficient conditions of stabilization are derived using the single Lyapunov-Krasovskii Functional (LKF). An example of a real plant is studied, and the comparison between LMI and LP approach is presented to show the advantages of the design procedure.
We propose two simple polynomial-time algorithms to find a positive solution to Ax = 0. Both algorithms iterate between coordinate descent steps similar to von Neumann's algorithm, and rescaling steps. In both cas...
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ISBN:
(数字)9783319334615
ISBN:
(纸本)9783319334615;9783319334608
We propose two simple polynomial-time algorithms to find a positive solution to Ax = 0. Both algorithms iterate between coordinate descent steps similar to von Neumann's algorithm, and rescaling steps. In both cases, either the updating step leads to a substantial decrease in the norm, or we can infer that the condition measure is small and rescale in order to improve the geometry. We also show how the algorithms can be extended to find a solution of maximum support for the system Ax = 0, x >= 0. This is an extended abstract. The missing proofs will be provided in the full version.
This paper describes a linear programming (LP) approach for solving the network utility maximization problem. The developed approach is inspired by a convex relaxation technique from nonconvex polynomial optimization ...
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ISBN:
(纸本)9781509013357
This paper describes a linear programming (LP) approach for solving the network utility maximization problem. The developed approach is inspired by a convex relaxation technique from nonconvex polynomial optimization methods. In contrast to most of the existing results where concavity of the network's utility function is often assumed, the proposed LP approach may still be used to solve the NUM problem even in the absence of such a concavity assumption. Although the presented LP approach is originally formulated to compute upper bounds for the global optima of the NUM problem, we illustrate through simulation examples that the obtained bounds often correspond to the exact global optima.
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