Non-Linear programming (NLP) problems are often encountered in real world applications. For such problems numerous algorithms have been proposed and the convergence properties of single run of these algorithms have ty...
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We introduce a symmetric dual pair for a class of nondifferentiable multi-objective fractional variational problems. Weak, strong, converse and self duality relations are established under certain invexity assumptions...
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We introduce a symmetric dual pair for a class of nondifferentiable multi-objective fractional variational problems. Weak, strong, converse and self duality relations are established under certain invexity assumptions. The paper includes extensions of previous symmetric duality results for multi-objective fractional variational problems obtained by Kim, Lee and Schaible [D.S. Kim, W.J. Lee, S. Schaible, Symmetric duality for invex multiobjective fractional variational problems, J. Math. Anal. Appl. 289 (2004) 505-521] and symmetric duality results for the static case obtained by Yang, Wang and Deng [X.M. Yang, S.Y. Wang, X.T. Deng, Symmetric duality for a class of multiobjective fractional programming problems, J. Math. Anal. Appl. 274 (2002) 279-2951 to the dynamic case. (c) 2006 Elsevier Inc. All rights reserved.
In this paper, we focus on the maximization of the height of jump of a serial link robot. The jump height maximization problem is formulated as a nonlinear programming problem, where torque patterns to drive joints in...
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In this paper, we focus on the maximization of the height of jump of a serial link robot. The jump height maximization problem is formulated as a nonlinear programming problem, where torque patterns to drive joints in the robot are decision variables and the objective function is an implicit function whose value is obtained as an output of a simulator. As a previous reasearch, an approximate solution method using a genetic algorithm was proposed. In the research, some interesting joint drive torque patterns were found by the method, but it costed much time to obtain a drive torque pattern. In order to shorten the computational time, in this paper, we propose a new solution method using a particle swarm optimization (PSO) technique.
A temporal flexible planning problem that involves contingent and requirement events can be formulated as a simple temporal network with uncertainty (STNU). An STNU is controllable when there is a strategy for executi...
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A temporal flexible planning problem that involves contingent and requirement events can be formulated as a simple temporal network with uncertainty (STNU). An STNU is controllable when there is a strategy for executing the requirement events (or actions) in such a way that all the conditions involving contingent events can be satisfied in all situations. The most interesting and useful controllability property is dynamic controllability in which the remaining actions in an STNU can always be scheduled under all possible feasible durations of future contingent events when all the past contingent events are known. In this paper, we propose and study a novel problem of assigning bounds on the duration of each requirement link in order for the resulting STNU to be dynamically controllable and to minimize the total cost over the allowed durations of all requirement links. We first prove the NP hardness of the problem with a linear cost function. We then formulate the dynamic controllability of an STNU as the constraints in a nonlinear optimization problem. Finally, we present methods for reducing the number of constraints in order to make the problem tractable and to demonstrate the computational performance of our methods.
The article deals with LINDO's integer programming. It also mentions that nonlinear programming gives rise to the application of integer programming even when linearization does not apply. Much of the technology o...
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The article deals with LINDO's integer programming. It also mentions that nonlinear programming gives rise to the application of integer programming even when linearization does not apply. Much of the technology of linear integer programming carries over to nonlinear optimization in order to find global optimal solutions. The extensions include preprocessing, cut generation, branch-and-bound for nonconvex functions and debug for nonlinear integer programs.
Consider a nondifferentiable convex MPEC problem with two variable vectors whose second variable vector belongs to the set of optimal solutions of the constraint problem. A sequential bundle method is constructed by c...
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Consider a nondifferentiable convex MPEC problem with two variable vectors whose second variable vector belongs to the set of optimal solutions of the constraint problem. A sequential bundle method is constructed by combining a proximal bundle method with a descent proximal level bundle method. The former is for providing a starting point at the beginning of each iteration and the latter is for finding approximate solutions generated in the sequential iterate process. The convergence analysis shows that under some conditions the algorithm presented can terminate at an approximate solution in finite steps according to a given tolerance error.
We discuss the implementation of a number of modern methods of global and nonsmooth continuous optimization, based oil the ideas of Rubinov, in a programming library GANSO. GANSO implements the derivative-free bundle ...
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We discuss the implementation of a number of modern methods of global and nonsmooth continuous optimization, based oil the ideas of Rubinov, in a programming library GANSO. GANSO implements the derivative-free bundle method, the extended cutting ailgle method, dynamical system-based optimization and their various combinations and heuristics. We outline the main ideas behind each method, and report oil the interfacing with Matlab and Maple packages.
The concepts of V-semilocal quasi b-preinvexity and V-semilocal strongly pseudo b-preinvexity are introduced for vector valued functions on the lines of Sudha Gupta [4]. They are used to establish duality results for ...
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We present a practical approach to Anstreicher and Lee's masked spectral bound for maximum-entropy sampling, and we describe favorable results that we have obtained with a Branch-and-Bound algorithm based on our a...
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We present a practical approach to Anstreicher and Lee's masked spectral bound for maximum-entropy sampling, and we describe favorable results that we have obtained with a Branch-and-Bound algorithm based on our approach. By representing masks in factored form, we are able to easily satisfy a semidefiniteness constraint. Moreover, this representation allows us to restrict the rank of the mask as a means for attempting to practically incorporate second-order information.
This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a method, based on nonlinear programming, for optimizing power g...
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ISBN:
(纸本)9781424421893
This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a method, based on nonlinear programming, for optimizing power generation efficiency. The proposed method considers not only that the hydroelectric power generation is a function of the water discharge and of the head, but also that the maximum power generation is head-dependent. Numerical results based on a realistic cascaded hydro system illustrate the proficiency of the proposed method.
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