linear programming models implemented in spreadsheets are understood to be difficult to reuse, whether with modified data that increases or decreases model scale (such as routine model maintenance), as well as with ne...
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linear programming models implemented in spreadsheets are understood to be difficult to reuse, whether with modified data that increases or decreases model scale (such as routine model maintenance), as well as with new data (such as deploying a model to a new business setting). The difficulty arises because spreadsheets commingle cell formulas with data, which requires editing cell formulas when the data changes. We provide a novel technique to implement a linear programming model in a spreadsheet that allows for full re-use of the spreadsheet code. It robustly accommodates modified or new data, and enables a spreadsheet LP easily to be reused or even deployed to a new setting with an entirely new dataset. This technique applies to any linear programming model up to approximately 1 million non-zero constraint coefficients, and operates in native Excel without use of macros or VBA. Spreadsheet LP models can now be re-used, re-deployed, and re-optimized as easily as with algebraic software. (C) 2018 Elsevier Ltd. All rights reserved.
Abdel-Basset et al. (Neural Computing and Applications, 2018, https://***/10.1007/s00521-018-3404-6) proposed methods for solving different types of neutrosophic linear programming problems (NLPPs) (NLPPs in which som...
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Abdel-Basset et al. (Neural Computing and Applications, 2018, https://***/10.1007/s00521-018-3404-6) proposed methods for solving different types of neutrosophic linear programming problems (NLPPs) (NLPPs in which some/all the parameters are represented as trapezoidal neutrosophic numbers (TrNNs)). Abdel-Basset et al. also pointed out that as a trapezoidal fuzzy number is a special case of trapezoidal neutrosophic number. Therefore, the fuzzy linear programming problems which can be solved by the existing methods (Ganesan andVeermani, Ann Oper Res, 2006, 143 : 305-315;Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395;Kumar et al., 2011, Appl Math Model, 35 : 817-823;Satti et al., Int J Decis Sci, 7 : 312-33) can also be solved by thier proposed method. In addition to that, to show the advantages of their proposed method over the existing methods (Ganesan and Veermani, Ann Oper Res, 2006, 143 : 305-315;Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395;Kumar et al., 2011, Appl Math Model, 35 : 817-823;Satti et al., Int J Decis Sci, 7 : 312-33), Abdel-Basset et al. solved the same fuzzy linear programming problems by their proposed method as well as the existing methods (Ganesan and Veermani, Ann Oper Res, 2006, 143 : 305-315;Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395;Kumar et al., 2011, Appl Math Model, 35 : 817-823;Satti et al., Int J Decis Sci, 7 : 312-33) and shown that the results, obtained on applying by their proposed method are better than the results, obtained on applying the existing methods (Ganesan and Veermani, Ann Oper Res, 2006, 143 : 305-315;Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395;Kumar et al., 2011, Appl Math Model, 35 : 817-823;Satti et al., Int J Decis Sci, 7 : 312-33). After a deep study of Abdel-Basset et al. 's method, it is observed that Abdel-Basset et al. have considered several mathematical incorrect assumptions in their proposed method and hence, it is scientifically inc
Heavy fault currents flow in the event of fault at the loads connected in distribution system. To protect these loads, circuit breakers and relays are required at appropriate places with proper coordination between th...
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Heavy fault currents flow in the event of fault at the loads connected in distribution system. To protect these loads, circuit breakers and relays are required at appropriate places with proper coordination between them. This research paper focuses on finding optimum relay setting required for minimum time to interrupt power supply to avoid miscoordination in operation of relays and also investigates effect on time multiplier settings (TMS) of directional overcurrent relays in a system with combined overhead lines-underground cables. linear programming problem (LPP) approach is used for optimization. It is interesting to know the quantitative variations in TMS as the underground cables have different characteristics than overhead lines.
We apply polynomial techniques (linear programming) to obtain lower and upper bounds on the covering radius of spherical designs as function of their dimension, strength, and cardinality. In terms of inner products we...
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Chamfer distances on the isometric grid are considered. A new method to compute the chamfer distances based on linear optimization is presented. In the LP model the starting pixel is the Origin, that is a triangle of ...
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Chamfer distances on the isometric grid are considered. A new method to compute the chamfer distances based on linear optimization is presented. In the LP model the starting pixel is the Origin, that is a triangle of the grid having co-ordinates (0, 0, 0). The co-ordinates of the end pixel of the path give the right-hand side of the model. The variables are the used numbers of the elementary steps. Each type of an elementary step has a uniquely defined weight. Our operational research approach determines the optimal paths as basic feasible solutions of a linear programming problem. We give directed graphs with feasible bases as nodes and arcs with conditions on the used weights such that the simplex method of linear programming may step from one feasible basis to another feasible basis. Thus, the possible course of the simplex method can be followed and the optimal bases can easily be captured. Thus, the final result of the analysis is an O(1) checking of the feasibility and optimality conditions. The optimal bases are summarized in a theorem which is the consequence of the general theory of linear programming. The method can be applied for other grids, but it needs to be adjusted for the particular grid.
作者：
Kitahara, TomonariSukegawa, NoriyoshiKyushu Univ
Fac Econ Dept Econ Engn Higashi Ku 6-19-1 Hakozaki Fukuoka Fukuoka 8128581 Japan Chuo Univ
Dept Informat & Syst Engn Fac Sci & Engn Bunkyo Ku 1-13-27 Kasuga Tokyo 1128551 Japan
Fujishige et al. propose the LP-Newton method, a new algorithm for linear programming problem (LP). They address LPs which have a lower and an upper bound for each variable, and reformulate the problem by introducing ...
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Fujishige et al. propose the LP-Newton method, a new algorithm for linear programming problem (LP). They address LPs which have a lower and an upper bound for each variable, and reformulate the problem by introducing a related zonotope. The LP-Newton method repeats projections onto the zonotope by Wolfe's algorithm. For the LP-Newton method, Fujishige et al. show that the algorithm terminates in a finite number of iterations. Furthermore, they show that if all the inputs are rational numbers, then the number of projections is bounded by a polynomial in L, where L is the input length of the problem. In this paper, we propose a modification to their algorithm using a binary search. In addition to its finiteness, if all the inputs are rational numbers and the optimal value is an integer, then the number of projections is bounded by L+1, that is, a linear bound.
Given that approximate quantum error-correcting (AQEC) codes have a potentially better performance than perfect quantum error correction codes, it is pertinent to quantify their performance. While quantum weight enume...
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In various efforts to secure the resilience of community, accurate reliability analysis of civil systems is critical considering their pivotal functions. As such systems generally consist of multiple components, their...
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In this study, a linear programming (l(1)-norm) sparse spike inversion (LPSSI) technique is used to estimate acoustic impedance distribution in the subsurface of the Blackfoot Field, Alberta, Canada. The aim of study ...
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In this study, a linear programming (l(1)-norm) sparse spike inversion (LPSSI) technique is used to estimate acoustic impedance distribution in the subsurface of the Blackfoot Field, Alberta, Canada. The aim of study is to determine high-resolution subsurface rock properties from the low-resolution seismic data and characterise the clastic Glauconitic channel. There are many traditional post-stack seismic inversion techniques available to estimate rock properties from seismic data, but LPSSI is a relatively simple and quick to compute subsurface model that can be used for qualitative as well as quantitative interpretation. The technique is applied in two steps;first, composite traces near to well locations are extracted and inverted for acoustic impedance, and comparison with well log impedance is used to optimise the LPSSI parameters. Analysis of the composite traces indicates that the algorithm has good performance with high correlation (0.97). In the second step, LPSSI is applied to the Blackfoot seismic data to estimate the distribution of acoustic impedance in the subsurface. Analysis of inverted acoustic impedance shows a low impedance anomaly ranging from 6500 to 8500 m/s*g/cc at the 1060-1075 ms time interval, which is characterised as a clastic Glauconitic sand channel. Thereafter, to confirm the sand channel, another important rock property, porosity, is estimated in the inter-well region using multi-attribute analysis. Analysis of the porosity shows the presence of a high porosity (15-22%) zone in the 1060-1075 ms time interval which coincides with the low impedance zone and confirms the presence of the sand channel.
In this work, we propose a predictor-corrector interior point method for linear programming in a primal-dual context, where the next iterate is chosen by the minimization of a polynomial merit function of three variab...
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In this work, we propose a predictor-corrector interior point method for linear programming in a primal-dual context, where the next iterate is chosen by the minimization of a polynomial merit function of three variables: the first is the steplength, the second defines the central path and the third models the weight of a corrector direction. The merit function minimization is performed by restricting it to constraints defined by a neighborhood of the central path that allows wide steps. In this framework, we combine different directions, such as the predictor, the corrector and the centering directions, with the aim of producing a better one. The proposed method generalizes most of predictor-corrector interior point methods, depending on the choice of the variables described above. Convergence analysis of the method is carried out, considering an initial point that has a good practical performance, which results in Q-linear convergence of the iterates with polynomial complexity. Numerical experiments using the Netlib test set are made, which show that this approach is competitive when compared to well established solvers, such as PCx.
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