This paper presents a simplified form of dual simplex algorithm for solving linear programming problems with fuzzy and neutrosophic numbers which supplies some great benefits over phase 1 of traditional dual simplex a...
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The objective of current investigation is to minimum the labor cost of staffs by using PI-LP and MI-LP. The price of tour is Rs.2000 for origin city and Rs.3000 for flight is in another city, rather than its origin ci...
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The objective of current investigation is to minimum the labor cost of staffs by using PI-LP and MI-LP. The price of tour is Rs.2000 for origin city and Rs.3000 for flight is in another city, rather than its origin city of tour. The price of tour is Rs.10,000 which is obtained in both the models. The method can also be used in mechanical engineering for transporting Problems and maximization problems.
Using the dual cone of sums of nonnegative circuits (SONC), we provide a relaxation of the global optimization problem to minimize an exponential sum and, as a special case, a multivariate real polynomial. Our approac...
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ISBN:
(纸本)9781450371001
Using the dual cone of sums of nonnegative circuits (SONC), we provide a relaxation of the global optimization problem to minimize an exponential sum and, as a special case, a multivariate real polynomial. Our approach builds on two key observations. First, that the dual SONC cone is contained in the primal one. Hence, containment in this cone is a certificate of nonnegativity. Second, we show that membership in the dual cone can be verified by a linear program. We implement the algorithm and present initial experimental results comparing our method to existing approaches.
linear programming was used for conjunctive use of canal water and groundwater to develop a cropping pattern for optimal net saving to the farmers in Bhagwanpur Distributary of the Eastern Gandak project. Constraints ...
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The adaptive linear programming (ALP) algorithm is an extension of the sequential linear programming algorithm where nonlinear formulations are iteratively approximated as linear formulations linearized about an itera...
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The purpose of this study was to determine the effect of Creative Problem Solving (CPS) on Higher Level Thinking Skills of Grade XI students in High Schools in linear Programs. This research was carried out in SMA Neg...
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The Lovasz theta number is a semidefinite programming bound on the clique number of (the complement of) a given graph. Given a vertex-transitive graph, every vertex belongs to a maximal clique, and so one can instead ...
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ISBN:
(数字)9781510629707
ISBN:
(纸本)9781510629707
The Lovasz theta number is a semidefinite programming bound on the clique number of (the complement of) a given graph. Given a vertex-transitive graph, every vertex belongs to a maximal clique, and so one can instead apply this semidefinite programming bound to the local graph. In the case of the Paley graph, the local graph is circulant, and so this bound reduces to a linear programming bound, allowing for fast computations. Impressively, the value of this program with Schrijver's nonnegativity constraint rivals the state-of-the-art closed-form bound recently proved by Hanson and Petridis. We conjecture that this linear programming bound improves on the Hanson-Petridis bound infinitely often, and we derive the dual program to facilitate proving this conjecture.
In this paper we introduce a new variant of station cone algorithm to solve linear programmimg problems. It uses a series of interior points Ok to determine the entering variables. The number of these interior points ...
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Computational equilibrium finding in large zerosum extensive-form imperfect-information games has led to significant recent AI breakthroughs. The fastest algorithms for the problem are new forms of counterfactual regr...
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Optimization techniques have been used in this paper to obtain an optimal investment in a selected portfolio that gives maximum returns with minimal inputs based on the secondary data supplied by a particular firm tha...
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Optimization techniques have been used in this paper to obtain an optimal investment in a selected portfolio that gives maximum returns with minimal inputs based on the secondary data supplied by a particular firm that is examined. Sensitivity analysis is done to ascertain the robustness of the resulting model towards the changes in input parameters to determine a redundant constraint using linear programming. The challenge of determining the available funds and allocating each component of the portfolio to maximize returns and minimize inputs by portfolio holders and managers who are the major decision-makers in allocating their resources cannot be quantified. This optimization technique is used to obtain an optimal investment portfolio including financial risks of a firm with disposable of $15,000,000.00 invested in crude oil, mortgage securities, cash crop, certificate of deposit, fixed deposit, treasury bills, and construction loans. The model is a single-objective model that maximizes the return on the portfolio as the interests on the original data reduces by 5%;then, the return on investments also reduced by almost 15%, with the quantum of money on treasury bills and construction loans posing a significant reduction for the maximum return. The investment in the other options saw a slight decrease. Also, as the interest rates of the original data increase by 5%, the return on investments also grows by almost 17% while the quantum of money on the treasury bills and construction loans increases, and the quantum of money on the other options experienced a decrease except for mortgage securities which recorded a slight increase.
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