Duality of linearprogramming is used to establish an important duality theorem for a class of non-linear programming problems. Primal problem has quasimonotonic objective function and a convex polyhedron as its const...
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作者：
Kalitventzeff, B.University of Liège
Belsim s.a. Centre Socran Parc industriel du Sart-Tilman 4900 (Angleur) Bat B6 4000 Liege Avenue Pré-Aily Belgium
This paper will focus on the application of MlNLP (Mixed Integer nonlinearprogramming). For the sake of application, we have chosen the utility network management problem which is important to mechanical and chemica...
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Maintenance budgeting refers to optimally allocating monetary resources so as to minimize the sum of (deterministic) preventive maintenance and (stochastic) corrective maintenance and unavailability costs. We propose ...
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ISBN:
(纸本)9781479913039
Maintenance budgeting refers to optimally allocating monetary resources so as to minimize the sum of (deterministic) preventive maintenance and (stochastic) corrective maintenance and unavailability costs. We propose a non-linear programming formulation for this problem, for a complex, multi-component system. Results of a case study for a combined cycle thermal power plant indicate the applicability of the proposed approach.
In this paper, a new algorithm has been introduced to construct the membership function and non-membership function of uncertain reliability of a series system via non-linear programming techniques, which having compo...
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ISBN:
(纸本)9783037855744
In this paper, a new algorithm has been introduced to construct the membership function and non-membership function of uncertain reliability of a series system via non-linear programming techniques, which having components following different types of intuitionistic uncertain failure rates.
Given the limitations of current hardware, the theoretical gains promised by quantum computing remain unrealized across practical applications. But the gap between theory and hardware is closing, assisted by developme...
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ISBN:
(纸本)9781665475365
Given the limitations of current hardware, the theoretical gains promised by quantum computing remain unrealized across practical applications. But the gap between theory and hardware is closing, assisted by developments in quantum algorithmic modeling. One such recent development is QuantumCircuitOpt (QCOpt), an open-source software framework that leverages state-of-the-art optimization-based solvers to find provably optimal compact circuit decompositions, which are exact up to global phase and machine precision. The quantum circuit design problem can be modeled using non-linear, non-convex constraints. However, QCOpt reformulates these non-linear constraints using well-known linearization techniques such that the resulting design problem is solved as a mixed-integer linearprogramming model. In this work, we instead explore whether the QCOpt's model could also be effective with a continuous non-linear programming (NLP) model obtained via relaxation of the integer variables in the non-linear constraints. We are able to present not only multiple significant enhancements to QCOpt, with up to 11.3x speed up in run times on an average, but also opportunities for more generally exploring the behavior of gradient-based NLP solvers.
The paper focuses on two topics, optimizing the proposed triangular tube for crashworthiness and solving a non-linear programming problem by a "mapping" technique, which the condition of Lagrange Multiplier ...
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The paper focuses on two topics, optimizing the proposed triangular tube for crashworthiness and solving a non-linear programming problem by a "mapping" technique, which the condition of Lagrange Multiplier Theorem is violated within the feasible region. The purpose of studying optimized triangular tubes is to prepare them for redesigning vehicle bumpers. The dimension optimization of triangular tube is carried out for its thickness and lateral length, based on the accomplished shape optimization under an impact. The load uniformity is taken as the objective function, which is defined as the ratio of maximum peak force and means crushing force. Meanwhile the mean crushing force and absorbed energy are treated as constraints. Based on FEA analysis, the regression functions for load uniformity, mean crushing force, and absorbed energy are formulated by RSM. The result has shown that triangular tube possesses an optimization region, under which the better-integrated property can be achieved to supply a more safety environment for vehicular occupants.
In this paper, we focus on solving non-linear programming (NLP) problems using quantum-behaved particle swarm optimization (QPSO). After a brief introduction to the original particle swarm optimization ( PSO), we desc...
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In this paper, we focus on solving non-linear programming (NLP) problems using quantum-behaved particle swarm optimization (QPSO). After a brief introduction to the original particle swarm optimization ( PSO), we describe the origin and development of QPSO, and the penalty function method for constrained NLP problems. The performance of QPSO is tested on some unconstrained and constrained benchmark functions and compared with PSO with inertia weight (PSO-In) and PSO with constriction factor (PSO-Co). The experimental results show that QPSO outperforms the traditional PSOs and is a promising optimization algorithm.
A computer code, FEASBL, is developed to maximize a non-linear objective function over a convex feasible region. The feasible region is defined by a set of non-linear and linear constraints on the variables. FEASBL ca...
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A computer code, FEASBL, is developed to maximize a non-linear objective function over a convex feasible region. The feasible region is defined by a set of non-linear and linear constraints on the variables. FEASBL can solve prob- lems involving up to fifty variables with a feasible region formed by up to fifty non-linear constraints, and fifty linear constraints. FEASBL uses a feasible direction method as its solution algorithm.
Converting power flow calculation of power system into the solution searching of a non-linear programming model. The divergence problem of ill-condition system calculation is settled. It is also a convenient way to ju...
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ISBN:
(纸本)9781424408276
Converting power flow calculation of power system into the solution searching of a non-linear programming model. The divergence problem of ill-condition system calculation is settled. It is also a convenient way to judge whether the general power flow calculation has feasible solutions or not. Get the correction equations by Newton method, LDLT decomposition method will be used to solve it. The coefficient matrix of correct equation is reordered by using AND reordering algorithm, thus the fill-in elements in LDLT decomposition is reduced significantly, which improves the calculating speed considerably. Proposed module and algorithm possess significant simplifying structure and can be implement or program easily with a novel vectorization expression. The adaptability and maintainability are improved greatly, too. Numerical simulations on test systems ranging in size from 118 to 1047 buses validate the correctness of the proposed model and method.
An adaptive mesh-free approach is developed to compute the lower bounds of limit loads in plane strain soil mechanics problems. There is no pre-defined connectivity between nodes in the mesh-free techniques, and this ...
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An adaptive mesh-free approach is developed to compute the lower bounds of limit loads in plane strain soil mechanics problems. There is no pre-defined connectivity between nodes in the mesh-free techniques, and this property facilitates the implementation of h-adaptivity. Nodes may be added, moved, or discarded without complex changes in the data structures involved. In this regard, the Shepard mesh-free method is used in conjunction with the nodal stress rate smoothing technique and the lower bound limit analysis theory to establish a non-linear optimization problem. This problem is solved by the second-order cone programming technique, and the result is a stress field that satisfies the lower bound requirements in a non-rigorous manner. The lack of rigorousness arises from relaxation during nodal stress rate smoothing process. An error estimator is introduced by the application of Taylor series expansion, and by controlling the local error via a user-de fined tolerance, the adaptive refinement strategy is established. To demonstrate the effectiveness of the proposed method, the procedure is applied to the examples of purely cohesive and cohesive-frictional soils. (C) 2017 Sharif University of Technology. All rights reserved.
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