Local convergence of an algorithm for solving optimal control problems

In this paper, a method is proposed for the numerical solution of optimal control problems with terminal equality constraints. The multiplier method is employed to deal with the terminal equality constraints. It is shown that a sequence of control functions, which converges to the optimal control, is obtained by the alternate update of control functions and multipliers.The authors wish to thank Dr. N. Fujii for his most valuable comments and suggestions.     

Asymptotic behavior of optimal solutions to control problems for systems described by differential inclusions corresponding to partial differential equations

In the paper, we consider differential inclusions related to PDEs of parabolic type and some control problems with integral cost functionals associated to them. Given a sequence of such problems, we investigate first the asymptotic behavior of solution sets (mild solutions or more precisely selection-trajectory pairs) for differential inclusions, and we get some semicontinuity or continuity results (Kuratowski convergence of solution sets). Then, we prove the -convergence of cost functionals, related to the above Kuratowski convergence of solution sets. Finally, applying the Buttazzo-Dal Maso abstract scheme, based on the sequential -convergence, we obtain results concerning the asymptotic behavior (hence, also stability results) for optimal solutions to control problems as well as the convergence of minimal values.The authors would like to thank Professors G. Dal Maso and S. Spagnolo for helpful conversations.This work was done when the first author was visiting ICTP and ISAS in Trieste in 1990/91.     

Reciprocal Optimal Control Problems and the Associated Pareto Frontier

It is well known that, if a control is Pareto optimal for a multiobjective optimal control problem, then it satisfies the necessary conditions of an optimal control problem with isoperimetric constraints. We introduce a set of sufficient conditions reversing that implication. Thus, we study some properties of the isoperimetric problems and their applications to the analysis of economic models.Research supported by the Ministry of Education, University, and Research of Italy and by the University of Padova.The authors thank the anonymous referee for suggestions that have added clarity to the exposition of the paper.     

A penalty optimization technique for a class of regulator problems

This paper describes a function space algorithm for the solution of a class of linear-quadratic optimal control problems.The research of the first author was supported by Senate Research Grant No. 8.187.17, University of Ilorin, Ilorin, Kwara State, Nigeria.The authors thank two anonymous referees for their useful and challenging suggestions and comments which improved the quality of this paper. The authors are also indebted to I. Orisamolu for carrying out the computing work.     

Numerical solution of linear least-squares problems with linear equality constraints

In Ref. 1, a perturbation theory for the linear least-squares problem with linear equality constraints is presented. In this paper, the condition numbers of a general formula given in Ref. 1 are examined in order to compare them with the condition numbers of the two matrices of the problem. A class of test problems is also defined to study experimentally the numerical stability of three algorithms.This work was partially supported by the Ministero della Pubblica Istruzione, Rome, Italy.The authors thank the Centro Interdipartimentale di Calcolo Automatico e di Informatica Applicata of the University of Modena for having provided computing time on its VAX computer.     

Convergence of a feasible directions algorithm for relaxed controls in time-lag systems

In this paper, we consider a class of time-lag optimal control problems involving control and terminal inequality constraints. A feasible direction algorithm has been obtained by Teo, Wong, and Clements for solving this class of optimal control problems. It was shown that anyL accumulation points of the sequence of controls generated by the algorithm satisfy a necessary condition for optimality. However, suchL accumulation points need not exist. The aim of this paper is to prove a convergence result, which ensures that the sequence of controls generated by the algorithm always has accumulation points in the sense of control measure, and these accumulation points satisfy a necessary condition for optimality for the corresponding relaxed problem.This work was done when the first author was on sabbatical leave at the School of Mathematics, University of New South Wales, Australia.     

One-armed bandit models with continuous and delayed responses

One-armed bandit processes with continuous delayed responses are formulated as controlled stochastic processes following the Bayesian approach. It is shown that under some regularity conditions, a Gittins-like index exists which is the limit of a monotonic sequence of break-even values characterizing optimal initial selections of arms for finite horizon bandit processes. Furthermore, there is an optimal stopping solution when all observations on the unknown arm are complete. Results are illustrated with a bandit model having exponentially distributed responses, in which case the controlled stochastic process becomes a Markov decision process, the Gittins-like index is the Gittins index and the Gittins index strategy is optimal. Acknowledgement.We thank an anonymous referee for constructive and insightful comments, especially those related to the notion of the Gittins index.Both authors are funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada.     

Optimal life strategies in organisms exposed to recurrent critical events

The optimal partition of energy between survival and reproduction is considered for a population subject to recurrent and potentially lethal critical events. The best strategy is found by maximizing fitness, a functional derived from the Lotka equation. The dynamics is governed by a second-order, age-varying, nonlinear system. The energy storage and the probability of survival are the state variables, while the amounts of energy placed into and withdrawn from the storage are the controls. The optimal life strategy is shown to be as follows: build up the storage at the very beginning of life, and then progressively deplete it to resist the critical events.This work was partially supported by MURST Project Ricerche sui Fondamenti della Conservazione della Natura. The authors would like to thank C. Ricci for suggesting the problem and C. Matessi for helpful discussion.     

一种具有非线性约束线性规划全局优化算法

本文提出了一种新的适用于处理非线性约束下线性规划问题的全局优化算法。该算法通过构造子问题来寻找优于当前局部最优解的可行解。该子问题可通过模拟退火算法来解决。通过求解一系列的子问题,当前最优解被不断地更新,最终求得全局最优解。最后,本算法应用于几个典型例题,并与罚函数法相比较,数值结果表明该算法是可行的,有效的。     

An algorithm for minimizing a class of locally Lipschitz functions

In this paper, we present an algorithm for minimizing a class of locally Lipschitz functions. The method generalized the -smeared method to a class of functions whose Clarke generalized gradients are singleton at almost all differentiable poinst. We analyze the global convergence of the method and report some numerical results.This work was supported by the National Science Foundation of China. The authors would like to thank the referees for their valuable comments, which led to significant improvements in the presentation.     

Generalized Solutions of Semilinear Parabolic Equations

It is well-known that a semilinear parabolic equation has no unique solution in the classical sense. We study such equations from the viewpoint of generalized functions. By using approximations for generalized functions, we obtain results on existence and uniqueness of generalized solutions. Furthermore, we establish the relationship between generalized solutions and classical solutions. Current address: Institute of Mathematics, University of Tsukuba, Tsukuba 305-8571, Japan     

A Simplicial Branch-and-Bound Method for Solving Nonconvex All-Quadratic Programs

In this paper we present an algorithm for solving nonconvex quadratically constrained quadratic programs (all-quadratic programs). The method is based on a simplicial branch-and-bound scheme involving mainly linear programming subproblems. Under the assumption that a feasible point of the all-quadratic program is known, the algorithm guarantees an -approximate optimal solution in a finite number of iterations. Computational experiments with an implementation of the procedure are reported on randomly generated test problems. The presented algorithm often outperforms a comparable rectangular branch-and-bound method.     

Maximal chains inωω and ultrapowers of the integers

Summary Various questions posed by P. Nyikos concerning ultrafilters on and chains in the partial order (, <^*) are answered. The main tool is the oracle chain condition and variations of it.The first author is partially supported by the basic research fund of the Israeli Academy. The second author is partially supported by NSERC and was a guest of Rutgers University while the research on this paper was being done. The authors would also like to thank P. Nyikos for his valuable comments on early versions of this paper. This is number 465 on the first author's list of publications     

Primal-Dual Simplex Method for Multiobjective Linear Programming

We develop a primal-dual simplex algorithm for multicriteria linear programming. It is based on the scalarization theorem of Pareto optimal solutions of multicriteria linear programs and the single objective primal-dual simplex algorithm. We illustrate the algorithm by an example, present some numerical results, give some further details on special cases and point out future research. The paper was written during a visit of the first author to the University of Sevilla financed by a grant of the Andalusian Consejería de Educación. The research of the first author was partially supported by University of Auckland Grant 3602178/9275. The research of the second and third authors was partially financed by Spanish Grants BFM2001-2378, BFM2001-4028, MTM2004-0909 and HA2003-0121. We thank Anthony Przybylski for the implementation and making his results available. We thank the anonymous referees, whose comments have helped us to improve the presentation of the paper.     

A note on the effect of numerical quadrature in finite element eigenvalue approximation

Summary In a recent work by the author and J.E. Osborn, it was shown that the finite element approximation of the eigenpairs of differential operators, when the elements of the underlying matrices are approximated by numerical quadrature, yield optimal order of convergence when the numerical quadrature satisfies a certain precision requirement. In this note we show that this requirement is indeed sharp for eigenvalue approximation. We also show that the optimal order of convergence for approximate eigenvectors can be obtained, using numerical quadrature with less precision.The author would like to thank Prof. I. Babuka for several helpful discussions. This work was done during the author's visit to the Institute of Physical Sciences and Technology and the Department of Mathematics of University of Maryland, College Park, MD 20742, USA, and was supported in part by the Office of Naval Research under Naval Research Grant N0001490-J-1030     

Parallelizable Preprocessing Method for Multistage Stochastic Programming Problems

Stochastic programming has extensive applications in practical problems such as production planning and portfolio selection. Typically, the model has very large size and some techniques are often used to exploit the special structure of the programs. It has been noticed that the coefficient matrix may not be of full rank in the well-known scenario formulation of stochastic programming; thus, the preprocessing is often necessary in developing rapid decomposition methods. In this paper, we propose a parallelizable preprocessing method, which exploits effectively the structure of the formulation. Although the underlying idea is simple, the method turns out to be very useful in practice, since it may help us to select the nonanticipativity constraints efficiently. Some numerical results are reported confirming the usefulness of the method.This work was partially supported by the Informatics Research Center for Development of Knowledge Society Infrastructure, Graduate School of Informatics, Kyoto University, Kyoto, Japan. The work of the first author was also supported in part by the National Science Foundation of China, Grant 10571039. The work of the second author was also supported in part by the Scientific Research Grant-in-Aid from the Japan Society for the Promotion of Science. The authors are grateful to the referees for careful reading of the paper and helpful comments.This author’s work was done while he was visiting Kyoto University.     

A new trust region method for nonlinear equations

In this paper, a new trust region method for the system of nonlinear equations is presented in which the determining of the trust region radius incorporates the information of its natural residual. The global convergence is obtained under mild conditions. Unlike traditional trust region method, the superlinear convergence of the method is proven under the local error bound condition. This condition is weaker than the nondegeneracy assumption which is necessary for superlinear convergence of traditional trust region method. We also propose an approximate algorithm for the trust region subproblem. Preliminary numerical experiments are reported. Acknowledgements.The authors are indebted to our supervisor, Professor Y.-X. Yuan, for his excellent guidance and Jorge J. Moré for his subroutine. And we would like to thank the referees for their valuable suggestions and comments.     

A continuation approach for the capacitated multi-facility weber problem based on nonlinear SOCP reformulation

We propose a primal-dual continuation approach for the capacitated multi-facility Weber problem (CMFWP) based on its nonlinear second-order cone program (SOCP) reformulation. The main idea of the approach is to reformulate the CMFWP as a nonlinear SOCP with a nonconvex objective function, and then introduce a logarithmic barrier term and a quadratic proximal term into the objective to construct a sequence of convexified subproblems. By this, this class of nondifferentiable and nonconvex optimization problems is converted into the solution of a sequence of nonlinear convex SOCPs. In this paper, we employ the semismooth Newton method proposed in Kanzow et al. (SIAM Journal of Optimization 20:297–320, 2009) to solve the KKT system of the resulting convex SOCPs. Preliminary numerical results are reported for eighteen test instances, which indicate that the continuation approach is promising to find a satisfying suboptimal solution, even a global optimal solution for some test problems.     

Finite element approximation to global stabilization of the Burgers’ equation by Neumann boundary feedback control law

In this article, we discuss global stabilization results for the Burgers’ equation using nonlinear Neumann boundary feedback control law. As a result of the nonlinear feedback control, a typical nonlinear problem is derived. Then, based on C ⁰-conforming finite element method, global stabilization results for the semidiscrete solution are analyzed. Further, introducing an auxiliary projection, optimal error estimates in \(L^{\infty }(L^{2})\), \(L^{\infty }(H^{1})\) and \(L^{\infty }(L^{\infty })\)-norms for the state variable are obtained. Moreover, superconvergence results are established for the first time for the feedback control laws, which preserve exponential stabilization property. Finally, some numerical experiments are conducted to confirm our theoretical findings.     

The unbalance and bounds on the average waiting time for periodic routing to one queue

In this paper we introduce the combinatorial notion of unbalance for a periodic zero-one splitting sequence. Using this unbalance we derive an upper bound for the average expected waiting time of jobs which are routed to one queue according to a periodic zero-one splitting sequence. In the companion paper [16] the upper bound will be extended to the routing to N parallel queues.Acknowledgement.The authors would like to thank Bruno Gaujal for his hospitality during their visits to LORIA, Nancy. During one of the stimulating discussions with him the graph order was found. The authors thank Robert Tijdeman for his helpful comments.