Newton`s iterates can converge to non-stationary points

In this note we discuss the convergence of Newton`s method for minimization. We present examples in which the Newton iterates satisfy the Wolfe conditions and the Hessian is positive definite at each step and yet the iterates converge to a non-stationary point. These examples answer a question posed by Fletcher in his 1987 book Practical methods of optimization.

Augmented Lagrangian methods under the constant positive linear dependence constraint qualification

Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.

Constructions of aggregation operators that preserve ordering of the data

We address the issue of identifying various classes of aggregation operators from empirical data, which also preserves the ordering of the outputs. It is argued that the ordering of the outputs is more important than the numerical values, however the usual data fitting methods are only concerned with fitting the values. We will formulate preservation of the ordering problem as a standard mathematical programming problem, solved by standard numerical methods.

Pectinase production by solid fermentation from Aspergillus niger by a new prescription experiment

The Ordos Plateau in China is covered with up to 300,000 ha of peashrub (Caragana) which is the dominant natural vegetation and ideal for fodder production. To exploit peashrub fodder, it is crucially important to optimize the culture conditions, especially culture substrate to produce pectinase complex. In this study, a new prescription process was developed. The process, based on a uniform experimental design, first optimizes the solid substrate and second, after incubation, applies two different temperature treatments (30 °C for the first 30 h and 23°C for the second 42 h) in the fermentation process. A multivariate regression analysis is applied to a number of independent variables (water, wheat bran, rice dextrose, ammonium sulfate, and Tween 80) to develop a predictive model of pectinase activity. A second-degree polynomial model is developed which accounts for an excellent proportion of the explained variation (R² = 97:7%). Using unconstrained mathematical programming, an optimized substrate prescription for pectinase production is subsequently developed. The mathematical analysis revealed that the optimal formula for pectinase production from Aspergillus niger by solid fermentation under the conditions of natural aeration, natural substrate pH (about 6.5), and environmental humidity of 60% is rice dextrose 8%, wheat bran 24%, ammonium sulfate ((NH₄)₂SO₄) 6%, and water 61%. Tween 80 was found to have a negative effect on the production of pectinase in solid substrate. With this substrate prescription, pectinase produced by solid fermentation of A. niger reached 36.3 IU/(g DM). Goats fed on the pectinase complex obtain an incremental increase of 0:47 kg day^-1 during the initial 25 days of feeding, which is a very promising new feeding prospect for the local peashrub. It is concluded that the new formula may be very useful for the sustainable development of arid and semiarid pastures such as those of the Ordos Plateau.

Bounded lower subdifferentiability optimization techniques : applications

In this article we develop a global optimization algorithm for quasiconvex programming where the objective function is a Lipschitz function which may have "flat parts". We adapt the Extended Cutting Angle method to quasiconvex functions, which reduces significantly the number of iterations and objective function evaluations, and consequently the total computing time. Applications of such an algorithm to mathematical programming problems inwhich the objective function is derived from economic systems and location problems are described. Computational results are presented.

Algoritmos para o problema de localização de uma facilidade com distâncias limitadas e restrições de atendimento

The objective in the facility location problem with limited distances is to minimize the sum of distance functions from the facility to the customers, but with a limit on each distance, after which the corresponding function becomes constant. The problem has applications in situations where the service provided by the facility is insensitive after a given threshold distance (eg. fire station location). In this work, we propose a global optimization algorithm for the case in which there are lower and upper limits on the numbers of customers that can be served

Otimização de escalas de serviço de tripulações estudo de caso em uma empresa de transporte urbano na região metropolitana de Natal/RN

This work aims to "build" rostering urban bus crews to minimize the cost of overtime. For this purpose a mathematical model was developed based on case study in an urban transport company in the metropolitan region of Natal. This problem is usually known in the literature as the Crew Scheduling Problem (CSP) and classified as NP-hard. The mathematical programming takes into account constraints such as: completion of all trips, daily and maximum allowable range of home and / or food. We used the Xpress-MP software to implement and validate the proposed model. For the tested instances the application of the model allowed a reduction in overtime from 38% to 84%

KT-invexity in optimal control problems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relação entre modelos de programação não-linear com incerteza no conjunto de restrições

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Programação linear por partes: revisão teórica e aplicações

Procura-se resgatar a importância de uma subárea da Programação Matemática conhecida como Programação Linear Por Partes - PLP. de fato a PLP tem inúmeras aplicações tanto na área teórica como em situações reais. Este trabalho apresenta os resultados de uma pesquisa bibliográfica, efetuada nas principais revistas técnicas e livros disponíveis relacionados com Pesquisa Operacional, que visou situar o estado da'arte da Programação Linear por Partes, bem como a abrangência de sua aplicabilidade. Particularmente, no contexto da PLP, este texto deslaca a Programação em Redes Lineares por Partes devido a sua relevância em muitas situações práticas.

Aggregation-based decomposition for multi-divisional models

The aggregation theory of mathematical programming is used to study decentralization in convex programming models. A two-level organization is considered and a aggregation-disaggregation scheme is applied to such a divisionally organized enterprise. In contrast to the known aggregation techniques, where the decision variables/production planes are aggregated, it is proposed to aggregate resources allocated by the central planning department among the divisions. This approach results in a decomposition procedure, in which the central unit has no optimization problem to solve and should only average local information provided by the divisions.

Algorithms for network piecewise-linear programs: A comparative study

Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

Modelo de otimização para seleção de árvores matrizes de Eucalyptus grandis

Individual data of basic density and volume of wood, pulp kappa number, soluble lignin, cost of pulping process as well as gravimetric gross yield of pulping process were used from 64 trees of Eucalyptus grandis W. Hill ex Maiden from a commercial population at Lençóis Paulista, SP. The Eucalyptus grandis's seeds were originally from a Seed Production Area (SPA) of Duratex S/A at Botucatu, SP. Obtained data were quantified considering objective of maximization no-bleaching pulp and volume and mass wood restriction, mass of residual and soluble lignin, planted area and pulping process cost. it has also been aimed a selection method for matrix trees through mathematical programming techniques. Obtained strategy maximized the economical result, selected matrix trees and followed all limits of technological and organizing productivities imposed by the company. It also aimed the production of no-bleaching pulp within the planned time.

Bound constrained smooth optimization for solving variational inequalities and related problems

Variational inequalities and related problems may be solved via smooth bound constrained optimization. A comprehensive discussion of the important features involved with this strategy is presented. Complementarity problems and mathematical programming problems with equilibrium constraints are included in this report. Numerical experiments are commented. Conclusions and directions of future research are indicated.

Branch and bound algorithm for transmission network expansion planning using DC model

This paper presents an algorithm to solve the network transmission system expansion planning problem using the DC model which is a mixed non-linear integer programming problem. The major feature of this work is the use of a Branch-and-Bound (B&B) algorithm to directly solve mixed non-linear integer problems. An efficient interior point method is used to solve the non-linear programming problem at each node of the B&B tree. Tests with several known systems are presented to illustrate the performance of the proposed method. ©2007 IEEE.