We use quadratic penalty functions along with some recent ideas from linear l1 estimation to arrive at a new characterization of primal optimal solutions in linear programs. The algorithmic implications of this analys...
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We use quadratic penalty functions along with some recent ideas from linear l1 estimation to arrive at a new characterization of primal optimal solutions in linear programs. The algorithmic implications of this analysis are studied, and a new, finite penalty algorithm for linear programming is designed. Preliminary computational results are presented.
This paper presents a general method to handle uncertainty to the Right Hand Side parameters of a linear programming (LP) model by means of Interval Type-2 Fuzzy Sets (IT2 FS) and trapezoidal membership functions. Fuz...
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ISBN:
(纸本)9781424423514
This paper presents a general method to handle uncertainty to the Right Hand Side parameters of a linear programming (LP) model by means of Interval Type-2 Fuzzy Sets (IT2 FS) and trapezoidal membership functions. Fuzzy linear programming (FLP) is a recent approach used on many situations where its optimal solution is provided by classical techniques as Simplex and Karmarkar algorithms. In this proposal, a LP problem with uncertain Right Side parameters treated as Interval Type-2 Fuzzy sets is solved by two optimization strategies. After the IT2 FS inference process, a real-valued solution should be found. In this way two methods are proposed to obtain optimal solutions when uncertain right hand side parameters exist, based on an alpha-cut optimality criterion.
linear programming is a foundational tool for many aspects of integer and combinatorial optimization. This work studies the complexity of solving linear programs exactly over the rational numbers through use of an ora...
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ISBN:
(纸本)9783030179533;9783030179526
linear programming is a foundational tool for many aspects of integer and combinatorial optimization. This work studies the complexity of solving linear programs exactly over the rational numbers through use of an oracle capable of returning limited-precision LP solutions. Under mild assumptions, it is shown that a polynomial number of calls to such an oracle and a polynomial number of bit operations, is sufficient to compute an exact solution to an LP. Previous work has often considered oracles that provide solutions of an arbitrary specified precision. While this leads to polynomial-time algorithms, the level of precision required is often unrealistic for practical computation. In contrast, our work provides a foundation for understanding and analyzing the behavior of the methods that are currently most effective in practice for solving LPs exactly.
There recently has been much interest in studying some optimization problems over symmetric cones. This paper deals with linear programming over symmetric cones （SCLP）. The objective here is to extend the Qi-Sun-Zho...
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There recently has been much interest in studying some optimization problems over symmetric cones. This paper deals with linear programming over symmetric cones （SCLP）. The objective here is to extend the Qi-Sun-Zhou＇s smoothing Newton algorithm to solve SCLP, where characterization of symmetric cones using Jordan algebras forms the fundamental basis for our analysis. By using the theory of Euclidean Jordan algebras, the authors show that the algorithm is globally and locally quadratically convergent under suitable assumptions. The preliminary numerical results for solving the second-order cone programming are also reported.
linear programming has the capability to optimize multilevel maintenance operations. Although addressed in maintainability documentation and papers for over 50 years, it is still not a commonly used tool. With the adv...
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ISBN:
(纸本)9781538628690
linear programming has the capability to optimize multilevel maintenance operations. Although addressed in maintainability documentation and papers for over 50 years, it is still not a commonly used tool. With the advent of Simplex Method Solvers in Excel, solutions to linear programming scenarios have become low cost and easily available. By addressing scenarios through identifying the primary goal and the constraints to the operations, linear programming is a highly useful tool for maintainability engineering and needs to be used on a more regular basis.
In the synthetic aperture radar (SAR) system, the traditional windowing method is usually adopted to keep the narrow mainlobe and low sidelobe level. However, it cannot make a balance between the mainlobe widening and...
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ISBN:
(纸本)9781665403696
In the synthetic aperture radar (SAR) system, the traditional windowing method is usually adopted to keep the narrow mainlobe and low sidelobe level. However, it cannot make a balance between the mainlobe widening and sidelobe suppression. This paper proposes a two-dimensional sidelobe suppression filter for SAR image, the sidelobe suprression is first modeled as a linear programming (LP) problem to estimate the filter weighting factors, and the convolution of the input signal and the filter sequence is then implemented to effectively suppress the sidelobe level without broadening the width of mainlobe. Simulation results show that the proposed method can suppress noise and sidelobe level from the imaging results.
We introduce a decoder for quantum CSS codes that is based on linear programming. Our definition is a priori slightly different from the one proposed by Li and Vontobel as we have a syndrome oriented approach instead ...
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ISBN:
(纸本)9781728159621
We introduce a decoder for quantum CSS codes that is based on linear programming. Our definition is a priori slightly different from the one proposed by Li and Vontobel as we have a syndrome oriented approach instead of an error oriented one, but we show that the success condition is equivalent. Although we prove that this decoder fails for quantum codes that do not have good soundness property (i.e., having large errors with syndrome of small weight) such as the toric code, we obtain good results from simulations. We run our decoder for hypergraph products of two random LDPC codes, showing that it performs better than belief propagation, even combined with the small-set-flip decoder that can provably correct a constant fraction of random errors.
A linear programming Monte Carlo method (LPMC) is proposed to achieve the optimal restoration of the whole degraded coastal wetland ecosystem, i.e. the minimum restoration cost, in the case of uncertain ecological res...
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A linear programming Monte Carlo method (LPMC) is proposed to achieve the optimal restoration of the whole degraded coastal wetland ecosystem, i.e. the minimum restoration cost, in the case of uncertain ecological restoration costs of different degraded coastal wetlands. LPMC can comprehensively and systematically complete the dynamic analysis of coastal wetland ecosystem restoration cost, including the uncertainty analysis of ecological restoration cost and the screening of equivalent robust solutions. The applicability of this method is demonstrated by solving a practical problem of ecological restoration of coastal wetlands. The results show that this method can generate the robust optimal solution block for the globally optimal objective function and decision variables under the condition of restoring cost uncertainty, including a variety of optimal solutions adapted to the different needs.
THE authors are concerned that linear programming recommendations to farmers often include more enterprises than make good sense. One reason recommendations may err in the direction of too many enterprises is that the...
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We employ signed measures that are positive definite up to certain degrees to establish Levenshtein-type upper bounds on the cardinality of codes with given minimum and maximum distance, and universal lower bounds on ...
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ISBN:
(纸本)9781538692912
We employ signed measures that are positive definite up to certain degrees to establish Levenshtein-type upper bounds on the cardinality of codes with given minimum and maximum distance, and universal lower bounds on the potential energy (for absolutely monotone interactions) for codes with given maximum distance and fixed cardinality. In particular, we extend the framework of Levenshtein bounds for such codes.
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