Annals of Operations Research

González-Lima, María

doi: 10.1007/s10479-008-0394-2pmid: N/A

Stamford da Silva, Alexandre; Campello de Souza, Fernando

doi: 10.1007/s10479-008-0360-zpmid: N/A

An optimal control approach is used to analyze the tradeoff between the use of water resources for electricity generation versus other economic uses (irrigation, industry, etc.). For that purpose, a dynamic model is presented which establishes relationships between economic growth, water resources management, and energy policy in the context of the aforementioned tradeoff, in an economy whose energy matrix is heavily dependent upon hydroelectric power. Among other results, the analysis establishes that in the market, the price of water for non-energy uses should be twice the price of the energy goods, indicating the necessity of substituting other sources of energy for hydroelectric power.

Amrouche, Nawel; Martín-Herrán, Guiomar; Zaccour, Georges

doi: 10.1007/s10479-008-0320-7pmid: N/A

We consider a noncooperative differential game where a retailer sells her own private label in addition to the manufacturer’s brand. We assume that each brand’s goodwill evolves according to a modified Nerlove-Arrow dynamics, in such a way that the advertising effort of one brand hurts the competitor’s goodwill stock. We characterize Feedback-Stackelberg pricing and advertising strategies and employ simulations to analyze their sensitivity to the main model parameters.

Janáček, Jaroslav; Buzna, Ľuboš

doi: 10.1007/s10479-008-0343-0pmid: N/A

This contribution is focused on an acceleration of branch and bound algorithms for the uncapacitated facility location problem. Our approach is based on the well-known Erlenkotters’ procedures and Körkels’ multi-ascent and multi-adjustment algorithms, which have proved to be the efficient tools for solving the large-sized instances of the uncapacitated facility location problem. These two original approaches were examined and a thorough analysis of their performance revealed how each particular procedure contributes to the computational time of the whole algorithms. These analyses helped us to focus our effort on the most frequent procedures. The unique contribution of this paper is a new dual ascent procedure. This procedure leads to considerable acceleration of the lower bound computation process and reduces the resulting computational time. To demonstrate more efficient performance of amended algorithms we present the results of extensive numerical experiments.

Hellwig, Klaus

doi: 10.1007/s10479-008-0345-ypmid: N/A

It is proposed to restrict the set of efficient solutions in multicriteria optimization by the requirement that a higher tradeoff of an objective should result in a higher output of the objective. It is shown that a solution satisfying this requirement exists under reasonable conditions.

Ruiz, Francisco; Rey, Lourdes; Muñoz, María

doi: 10.1007/s10479-008-0346-xpmid: N/A

In this paper, a graphical characterization, in the decision space, of the properly efficient solutions of a convex multiobjective problem is derived. This characterization takes into account the relative position of the gradients of the objective functions and the active constraints at the given feasible solution. The unconstrained case with two objective functions and with any number of functions and the general constrained case are studied separately. In some cases, these results can provide a visualization of the efficient set, for problems with two or three variables. Besides, a proper efficiency test for general convex multiobjective problems is derived, which consists of solving a single linear optimization problem.

Avkiran, Necmi; Tone, Kaoru; Tsutsui, Miki

doi: 10.1007/s10479-008-0356-8pmid: N/A

Data envelopment analysis (DEA) has been utilized worldwide for measuring efficiencies of banks, telecommunications, electric utilities and so forth. Yet, the existing models have some well-known shortcomings that limit their usefulness. In DEA we have two fundamental approaches to measuring efficiency with very different characteristics; radial and non-radial. We demonstrate a method for linking these two approaches in a unified framework called Connected-SBM (slacks-based measure). It includes two scalar parameters, and by changing the parameter values we can relocate the analysis anywhere between the radial and the non-radial models. An appropriate choice of these parameters can overcome the key shortcomings inherent in the two approaches, namely, proportionality and mixed patterns of slacks.

Yan, Wei; Li, Shurong

doi: 10.1007/s10479-008-0398-ypmid: N/A

Considering the stochastic exchange rate, a four-factor futures model with the underling asset, convenience yield, instantaneous risk free interest rate and exchange rate, is established. These processes follow jump-diffusion processes (Weiner process and Poisson process). The corresponding partial differential equation (PDE) of the futures price is derived. The general solution of the PDE with parameters is drawn. The weight least squares approach is applied to obtain the parameters of above PDE. Variance is substituted by semi-variance in Markowitzs portfolio selection model. Therefore, a class of multi-period semi-variance model is formulated originally. Then, a continuous-time mean-variance portfolio model is also considered. The corresponding stochastic Hamilton-Jacobi-Bellman (HJB) equation of the problem with nonlinear constraints is derived. A numerical algorithm is proposed for finding the optimal solution in this paper. Finally, in order to demonstrate the effectiveness of the theoretical models and numerical methods, the fuel futures in Shanghai exchange market and the Brent crude oil futures in London exchange market are selected to be examples.

Wang, Fusheng; Zhang, Kecun

doi: 10.1007/s10479-008-0401-7pmid: N/A

In this paper, a hybrid algorithm for solving finite minimax problem is presented. In the algorithm, we combine the trust-region methods with the line-search methods and curve-search methods. By means of this hybrid technique, the algorithm, according to the specific situation at each iteration, can adaptively performs the trust-region step, line-search step or curve-search step, so as to avoid possibly solving the trust-region subproblems many times, and make better use of the advantages of different methods. Moreover, we use second-order correction step to circumvent the difficulties of the Maratos effect occurred in the nonsmooth optimization. Under mild conditions, we prove that the new algorithm is of global convergence and locally superlinear convergence. The preliminary experiments show that the new algorithm performs efficiently.

Dayar, Tuǧrul; Meriç, Akın

doi: 10.1007/s10479-008-0429-8pmid: N/A

Two approximative fixed-point iterative methods based on decomposition for closed queueing networks with Coxian service distributions and arbitrary buffer sizes are extended to include phase-type service distributions. The irreducible Markov chain associated with each subnetwork in the respective decompositions is represented hierarchically using Kronecker products. The two methods are implemented in a software tool capable of computing the steady-state probability vector of each subnetwork by a multilevel method at each fixed-point iteration and are compared with other methods for accuracy and efficiency. Numerical results indicate that there is a niche filled by the two approximative methods.