Identification of multiple-input single-output Hammerstein models using Bezier curves and Bernstein polynomials

This paper considers the implementation of Bezier–Bernstein polynomials and the Levenberg–Marquart algorithm for identifying multiple-input single-output (MISO) Hammerstein models consisting of nonlinear static functions followed by a linear dynamical subsystem. The nonlinear static functions are approximated by the means of Bezier curves and Bernstein basis functions. The identification method is based on a hybrid scheme including the inverse de Casteljau algorithm, the least squares method, and the Levenberg–Marquart (LM) algorithm. Furthermore, results based on the proposed scheme are given which demonstrate substantial identification performance.     

Application of a dynamic market inverse elasticity law with linear and log-linear demand models

In this paper we will evaluate the significance of the inclusion of “dynamics” in profit maximization for widely used demand functions. Specifically we will consider both linear and log-linear demand models. Using these demand functions we will obtain closed form solutions for optimum prices (dynamic market inverse elasticity laws). The optimum price in a market governed by dynamic demand response is different from the one within a static response framework; we will relate the differences to specific characteristics of the demand function. One focus of this work will be to develop intuitive explanations for our conclusion regarding the relative size of the optimum price in static and dynamic markets. This work was completed when the author was with Bell Laboratories, USA.     

Merger effect of two firms under network equilibrium

This paper studies the merger effect of two firms under the price competition of n firms, represented by n nodes on a linear network equilibrium model. The difference of profits between pre- and post-merger of the two firms can be described explicitly in terms of the substitution matrix. In general, the evaluation of the merger effect requires the knowledge of the substitution effects among all n nodes. For some interesting special cases, however, we obtain simple qualitative results. Specifically, the profitability of the merger can be predicted from the substitution effect of the two firms. Numerical examples exhibit the usefulness of our results.     

Update of corrected stiffness and mass matrices based on measured dynamic modal data

The physical parameters obtained from modal tests do not satisfy the dynamic constraints of eigenvalue function and orthogonality requirements due to modeling and measurement errors. The purpose of this study is to present the analytical equations on the updated stiffness and mass matrices in the satisfaction of such dynamic constraints. Minimizing the cost functions of the difference between analytical and desired physical parameter matrices, the corrected parameter matrices are straightforwardly derived by utilizing the Moore–Penrose inverse without using any multipliers. The cost functions given by a few researchers are utilized. From the comparison of the existing analytical results and the proposed equations, the validity of the proposed methods is evaluated in an application.     

An interval portfolio selection problem based on regret function

Recent mergers in the banking industry have often generated disappointing shareholder returns. Delays in implementing potential operating savings and realizing benefits of scale economies may be one reason these mergers have disappointing returns. Using data envelopment analysis (DEA), we analyze a 200-branch network formed in a merger of four banks. The operating efficiency of each branch is benchmarked against “best-practice” branches in the combined merged bank as well as “best practice” branches within each pre-merger bank. This analysis identified opportunities to reduce branch operating costs by 22 percent for the entire merged bank. In contrast, the cost savings opportunity is under seven percent when analyzed within each pre-merger bank.These findings suggest benchmarking across the entire merged bank to identify the best practices bank-wide can generate added savings. However, in this bank merger, these merger benefits were not realized until four years after the merger. Interviews with key players in the merged bank indicate that the bank deferred realizing these benefits because of political pressures, personnel integration issues, system integration issues, and financial components of the merger such as restructuring reserves and the purchase price. These causes suggest areas where shareholders can and should demand more rapid improvement in performance of bank mergers and areas for future corporate merger research.     

Formulation and analysis of horizontal mergers among oligopolistic firms with insights into the merger paradox: a supply chain network perspective

In this paper, we consider oligopolistic firms with supply chain networks who are involved in the production, storage, and distribution of a homogeneous product to demand markets and explore what has become known in the literature as the “merger paradox.” We present the oligopolistic supply chain network equilibrium model associated with the competing firms before the horizontal mergers and also develop the supply chain network optimization model post the complete merger. In addition, we develop the model in which only a subset of the firms in the industry merge. The governing concept of the competing firms is that of Cournot–Nash equilibrium. We utilize finite-dimensional variational inequality theory for the formulation, analysis, and solution of both the pre and the post-merger supply chain network problems. We provide numerical examples for which we compute the total costs, the total revenues, as well as the profits obtained for the firms pre and post the mergers for a variety of distinct oligopoly problems. The generality of the network models and the flexibility of the computational approach, which yields closed form expressions for the product flows at each iteration, allows us to obtain deeper insights into the merger paradox.     

Symmetry in RLT-type relaxations for the quadratic assignment and standard quadratic optimization problems

The reformulation–linearization technique (RLT), introduced in [Sherali, H. D., Adams. W. P. (1990). A hierarchy of relaxations between the continuous and convex hull representations for zero-one programming problems. SIAM Journal on Discrete Mathematics 3(3), 411–430], provides a way to compute a hierarchy of linear programming bounds on the optimal values of NP-hard combinatorial optimization problems. In this paper we show that, in the presence of suitable algebraic symmetry in the original problem data, it is sometimes possible to compute level two RLT bounds with additional linear matrix inequality constraints. As an illustration of our methodology, we compute the best-known bounds for certain graph partitioning problems on strongly regular graphs.     

A note on equilibria for two-tier supply chains with a single manufacturer and multiple retailers

A well-studied problem in the supply chain management literature considers a two-tier supply chain for a homogeneous product with a single manufacturer, multiple retailers and a general inverse demand function. The problem has been analyzed in the literature without a formal mathematical treatment of the existence/uniqueness of equilibria. Furthermore, the existence/uniqueness results derived for related models are not extendable to our model. The objective of this paper is to derive sufficient conditions for the existence/uniqueness of Stackelberg–Nash–Cournot equilibria for the two-tier problem.     

Do mergers enhance the performance of hospital efficiency?

Due to the wave of mergers that have taken place in the USA, the early 1990s could be labelled as a restructuring era for health care systems. The question of whether mergers have an impact on organizational performance is still an area of interest for health services researchers. In this study, we examined the impacts of horizontal mergers of US hospital's technical efficiency before and after merger using longitudinal Data Envelopment Analysis (DEA). The findings of our study illustrate that mergers do increase a hospital's level of efficiency. Constant returns-to-scale model indicated an overall reduction in input utilisation after merger, compared to variable returns-to-scale model. This indicates the role of scale efficiency as a dominant source of improvement in inefficiency of hospitals involved in horizontal mergers, but not for technical efficiency. Suggestions for future study are provided.     

Dynamic maintenance decision-making for series–parallel manufacturing system based on MAM–MTW methodology

Proper maintenance schedule is required to improve manufacturing systems’ profitability and productivity. A novel dynamic maintenance strategy is thus developed to incorporate both the single-machine optimization and the whole-system schedule for series–parallel system. Firstly, multiple attribute value theory and maintenance effects are considered in the single-machine optimization. A developed multi-attribute model (MAM) is used to determine the optimal maintenance intervals. Then, a series–parallel structure of the system is investigated in terms of the whole-system schedule. Maintenance time window (MTW) programming is presented to make a cost-effective system schedule by dynamically utilizing maintenance opportunities. The maintenance scheme achieved by using the proposed MAM–MTW methodology is demonstrated through a case study in a hydraulic steering factory. It is concluded that proper consideration of maintenance effects and time window leads to a significant cost reduction.     

Limit problems for interpolation by analytic radial basis functions

Interpolation problems for analytic radial basis functions like the Gaussian and inverse multiquadrics can degenerate in two ways: the radial basis functions can be scaled to become increasingly flat, or the data points coalesce in the limit while the radial basis functions stay fixed. Both cases call for a careful regularization, which, if carried out explicitly, yields a preconditioning technique for the degenerating linear systems behind these interpolation problems. This paper deals with both cases. For the increasingly flat limit, we recover results by Larsson and Fornberg together with Lee, Yoon, and Yoon concerning convergence of interpolants towards polynomials. With slight modifications, the same technique can also handle scenarios with coalescing data points for fixed radial basis functions. The results show that the degenerating local Lagrange interpolation problems converge towards certain Hermite–Birkhoff problems. This is an important prerequisite for dealing with approximation by radial basis functions adaptively, using freely varying data sites.     

The least squares spectral element method for the Cahn–Hilliard equation

The problem of numerically resolving an interface separating two different components is a common problem in several scientific and engineering applications. One alternative is to use phase field or diffuse interface methods such as the Cahn–Hilliard (C–H) equation, which introduce a continuous transition region between the two bulk phases. Different numerical schemes to solve the C–H equation have been suggested in the literature. In this work, the least squares spectral element method (LS-SEM) is used to solve the Cahn–Hilliard equation. The LS-SEM is combined with a time–space coupled formulation and a high order continuity approximation by employing C¹¹p-version hierarchical interpolation functions both in space and time. A one-dimensional case of the Cahn–Hilliard equation is solved and the convergence properties of the presented method analyzed. The obtained solution is in accordance with previous results from the literature and the basic properties of the C–H equation (i.e. mass conservation and energy dissipation) are maintained. By using the LS-SEM, a symmetric positive definite problem is always obtained, making it possible to use highly efficient solvers for this kind of problems. The use of dynamic adjustment of number of elements and order of approximation gives the possibility of a dynamic meshing procedure for a better resolution in the areas close to interfaces.     

The generalized Dirichlet–Neumann map for linear elliptic PDEs and its numerical implementation

A new approach for analyzing boundary value problems for linear and for integrable nonlinear PDEs was introduced in Fokas [A unified transform method for solving linear and certain nonlinear PDEs, Proc. Roy. Soc. London Ser. A 53 (1997) 1411–1443]. For linear elliptic PDEs, an important aspect of this approach is the characterization of a generalized Dirichlet to Neumann map: given the derivative of the solution along a direction of an arbitrary angle to the boundary, the derivative of the solution perpendicularly to this direction is computed without solving on the interior of the domain. This is based on the analysis of the so-called global relation, an equation which couples known and unknown components of the derivative on the boundary and which is valid for all values of a complex parameter k. A collocation-type numerical method for solving the global relation for the Laplace equation in an arbitrary bounded convex polygon was introduced in Fulton et al. [An analytical method for linear elliptic PDEs and its numerical implementation, J. Comput. Appl. Math. 167 (2004) 465–483]. Here, by choosing a different set of the “collocation points” (values for k), we present a significant improvement of the results in Fulton et al. [An analytical method for linear elliptic PDEs and its numerical implementation, J. Comput. Appl. Math. 167 (2004) 465–483]. The new collocation points lead to well-conditioned collocation methods. Their combination with sine basis functions leads to a collocation matrix whose diagonal blocks are point diagonal matrices yielding efficient implementation of iterative methods; numerical experimentation suggests quadratic convergence. The choice of Chebyshev basis functions leads to higher order convergence, which for regular polygons appear to be exponential.     

Estimation of parameter matrices based on measured data

Finite element structural updating based on measured data may inherent significant errors due to uncertainties in the updated physical parameter matrices. This study presents analytical equations to estimate the change in the physical parameter matrices based on the measured modal data of dynamic systems and the measured displacement data of static systems. The equations for the parameter estimation are derived by minimizing cost functions in the satisfaction of the eigenvalue equation, the mode shape orthogonality requirements for the dynamic system, and the satisfaction of the measured displacement data for the static systems. The proposed method utilizes the Moore–Penrose inverse for the inverse of the rectangular matrices without using Lagrange multipliers. Comparing the analytical results with Berman & Nagy’s method and Yang & Chen’s method, this study demonstrates that the derived equations take simpler forms and produce more accurate results. The proposed method can be widely utilized in predicting static or dynamic parameter matrices for the design and analysis of any structure.     

Correction of stiffness and mass matrices utilizing simulated measured modal data

Measured and analytical data are unlikely to be equal due to measured noise, model inadequacies and structural damage, etc. It is necessary to update the physical parameters of analytical models for proper simulation and design studies. Starting from simulated measured modal data such as natural frequencies and their corresponding mode shapes, this study presents the equations to update the physical parameters of stiffness and mass matrices simultaneously for analytical modelling by minimizing a cost function in the satisfaction of the dynamic constraints of orthogonality requirement and eigenvalue function. The proposed equations are straightforwardly derived by Moore–Penrose inverse matrix without using any multipliers. The cost function is expressed by the sum of the quadratic forms of both the difference between analytical and updated mass, and stiffness matrices. The results are compared with the updated mass matrix to consider the orthogonality requirement only and the updated stiffness matrix to consider the eigenvalue function only, respectively. Also, they are compared with Wei’s method which updates the mass and stiffness matrices simultaneously. The validity of the proposed method is illustrated in an application to correct the mass and stiffness matrices due to section loss of some members in a simple truss structure.     

Decent flow methods for inverse Sturm–Liouville problem

In this paper, we propose three numerical methods for the inverse Sturm–Liouville operator in impedance form. We use a finite difference method to discretize the Sturm–Liouville operator and expand the impedance function with some basis functions. The correction technique is discussed. By solving an un-weighted least squares problem, we find an approximation to the impedance function. Numerical experiments are presented to show the accuracy and stability of the numerical methods.     

Approximate general and explicit solutions of nonlinear BBMB equations by Exp-Function method

In this work, we implement a relatively new analytical technique, the Exp-Function method, for solving special form of generalized nonlinear Benjamin–Bona–Mahony–Burgers equation (BBMB) which may contain high nonlinear terms.     

Dynamic extension problems concerning asymmetrical mode III crack

By application of the method of complex variable function, dynamic extension problems on the surfaces of asymmetrical mode III crack subjected to shear loads were researched. Universal expressions of analytical solutions were attained by the approaches of self-similar functions. The problems considered can be facilely transformed into Riemann–Hilbert problems in terms of this technique, and analytical solutions of the stress, the displacement and dynamic stress intensity factor under the actions of unlike loads P and Pt located at the origin of the coordinates respectively, were acquired. In the light of corresponding material properties, the variable rule of dynamic stress intensity factor was depicted very well. By those solutions gained and superposition principle, the solutions of discretionarily intricate problems can be obtained.     

Integrated portfolio management with options

In this paper we examine the problem of managing portfolios consisting of both, stocks and options. For the simultaneous optimization of stock and option positions we base our analysis on the generally accepted mean–variance framework. First, we analyze the effects of options on the mean–variance efficient frontier if they are considered as separate investment alternatives. Due to the resulting asymmetric portfolio return distribution mean–variance analysis will be not sufficient to identify optimal optioned portfolios. Additional investor preferences which are expressed in terms of shortfall constraints allow a more detailed portfolio specification. Under a mean–variance and shortfall preference structure we then derive optioned portfolios with a maximum expected return. To circumvent the technical optimization problems arising from stochastic constraints we use an approximation of the return distribution and develop economically meaningful conditions under which the complex optimization problem can be transformed into a linear problem being comparably easy to solve. Empirical results based on both, empirical market data and Monte Carlo simulations, illustrate the portfolio optimization procedure with options.     

Recent developments in dynamic advertising research

A variety of continuous-time differential functions have been developed to investigate dynamic advertising problems in business and economics fields. Since major dynamic models appearing before 1995 have been reviewed by a few survey papers, we provide a comprehensive review of the dynamic advertising models published after 1995, which are classified into six categories: (i) Nerlove–Arrow model and its extensions, (ii) Vidale–Wolfe model and its extensions, (iii) Lanchester model and its extensions, (iv) the diffusion models, (v) dynamic advertising-competition models with other attributes, and (vi) empirical studies for dynamic advertising problems. For each category, we first briefly summarize major relevant before-1995 models, and then discuss major after-1995 models in details. We find that the dynamic models reviewed in this paper have been extensively used to analyze various advertising problems in the monopoly, duopoly, oligopoly, and supply chain systems. Our review reveals that the diffusion models have not been used to analyze advertising problems in supply chain operations, which may be a research direction in the future. Moreover, we learn from our review that very few publications regarding dynamic advertising problems have considered the supply chain competition. We also find that very few researchers have used the diffusion model to investigate the dynamic advertising problems with product quality as a decision variable; and, the pricing decision has not been incorporated into any extant Lanchester model. The paper ends with a summary of our review and suggestions on possible research directions in the future.