Optimal on-line algorithms for one batch machine with grouped processing times

In this paper, we study on-line scheduling problems on a batch machine with the assumption that all jobs have their processing times in [p, (1+φ)p], where p>0 and \(\phi=(\sqrt{5}-1)/2\). Jobs arrive over time. First, we deal with the on-line problem on a bounded batch machine with the objective to minimize makespan. A class of algorithms with competitive ratio \((\sqrt{5}+1)/2\) are given. Then we consider the scheduling on an unbounded batch machine to minimize the time by which all jobs have been delivered, and provide a class of on-line algorithms with competitive ratio \((\sqrt{5}+1)/2\). The two class of algorithms are optimal for the problems studied here.     

On the Diaconis-Gangolli Markov chain for sampling contingency tables with cell-bounded entries

The problems of uniformly sampling and approximately counting contingency tables have been widely studied, but efficient solutions are only known in special cases. One appealing approach is the Diaconis and Gangolli Markov chain which updates the entries of a random 2×2 submatrix. This chain is known to be rapidly mixing for cell-bounded tables only when the cell bounds are all 1 and the row and column sums are regular. We demonstrate that the chain can require exponential time to mix in the cell-bounded case, even if we restrict to instances for which the state space is connected. Moreover, we show the chain can be slowly mixing even if we restrict to natural classes of problem instances, including regular instances with cell bounds of either 0 or 1 everywhere, and dense instances where at least a linear number of cells in each row or column have non-zero cell-bounds.     

On domination number of Cartesian product of directed paths

Let γ(G) denote the domination number of a digraph G and let P _m □P _n denote the Cartesian product of P _m and P _n , the directed paths of length m and n. In this paper, we give a lower and upper bound for γ(P _m □P _n ). Furthermore, we obtain a necessary and sufficient condition for P _m □P _n to have efficient dominating set, and determine the exact values: γ(P ₂□P _n )=n, g(P₃\square P_n)=n+é\fracn4ù\gamma(P_{3}\square P_{n})=n+\lceil\frac{n}{4}\rceil, g(P₄\square P_n)=n+é\frac2n3ù\gamma(P_{4}\square P_{n})=n+\lceil\frac{2n}{3}\rceil, γ(P ₅□P _n )=2n+1 and g(P₆\square P_n)=2n+é\fracn+23ù\gamma(P_{6}\square P_{n})=2n+\lceil\frac{n+2}{3}\rceil.     

Stress and Leadership Tendencies of Respondents from Iran: Exploring Similarities and Differences Based on Age and Gender

The leadership tendencies of people are likely to be influenced by their cultural contexts. For example, it is expected that people from high-context cultures are likely to be more focused on relationships. To explore the behavioral tendencies of working adults in the cities of Tehran and Kerman, this pilot study focused on comparing the leadership and stress perceptions of 228 Iranian respondents based on their age and gender. These respondents have a significantly higher score on relationship orientation. On the other side, the younger respondents from Iran had a significantly higher score on the stress overload perception. Practical suggestions for expatriates and implications for future studies are presented.     

A linear programming duality approach to analyzing strictly nonblocking <Emphasis Type="Italic">d</Emphasis>-ary multilog networks under general crosstalk constraints

When a switching network topology is used for constructing optical cross-connects, as in the circuit switching case, no two routes are allowed to share a link. However, if two routes share too many switching elements, then crosstalk introduced at those switching elements degrades signal quality. Vaez and Lea (IEEE Trans. Commun. 48:(2)316–323, 2000) introduced a parameter c which is the maximum number of distinct switching elements a route can share with other routes in the network. This is called the general crosstalk constraint. This paper presents a new method of analyzing strictly nonblocking multi-log networks under this general crosstalk constraint using linear programming duality.     

New perspectives on the governance of executive compensation: an examination of the role and effect of compensation consultants

We develop a multi-theoretic approach, drawing on economic, institutional, managerial power and social comparison literatures to explain the role of the external compensation consultant in the top management pay setting institutional field. Taking advantage of recent disclosure requirements in the UK, we collect data on compensation consultant use in 232 large companies. We show that consultants are a prevalent part of the CEO pay setting scene, and document evidence of all advisor use. Our econometric results show that consultant use is associated with firm size and the equity pay mix. We also show that CEO pay is positively associated with peer firms that share consultants, with higher board and consultant interlocks, and some evidence that where firms supply other business services to the firm, CEO pay is greater.     

The potential of integrated modelling in conservation biology: A case study of the black‐footed albatross (Phoebastria nigripes)

Conservation biology aims at assessing the status of a population, based on information which is often incomplete. Integrated population modelling based on state‐space models appears to be a powerful and relevant way of combining into a single likelihood several types of information such as capture‐recapture data and population surveys. In this paper, the authors describe the principles of integrated population modelling and they evaluate its performance for conservation biology based on a case study, that of the black‐footed albatross, a northern Pacific albatross species suspected to be impacted by longline fishing     

Small area estimation: the EBLUP estimator based on spatially correlated random area effects

This paper deals with small area indirect estimators under area level random effect models when only area level data are available and the random effects are correlated. The performance of the Spatial Empirical Best Linear Unbiased Predictor (SEBLUP) is explored with a Monte Carlo simulation study on lattice data and it is applied to the results of the sample survey on Life Conditions in Tuscany (Italy). The mean squared error (MSE) problem is discussed illustrating the MSE estimator in comparison with the MSE of the empirical sampling distribution of SEBLUP estimator. A clear tendency in our empirical findings is that the introduction of spatially correlated random area effects reduce both the variance and the bias of the EBLUP estimator. Despite some residual bias, the coverage rate of our confidence intervals comes close to a nominal 95%.     

Computational methods for complex stochastic systems: a review of some alternatives to MCMC

We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situations they can be difficult to implement; and suffer from problems such as poor mixing, and the difficulty of diagnosing convergence. Here we review three alternatives to MCMC methods: importance sampling, the forward-backward algorithm, and sequential Monte Carlo (SMC). We discuss how to design good proposal densities for importance sampling, show some of the range of models for which the forward-backward algorithm can be applied, and show how resampling ideas from SMC can be used to improve the efficiency of the other two methods. We demonstrate these methods on a range of examples, including estimating the transition density of a diffusion and of a discrete-state continuous-time Markov chain; inferring structure in population genetics; and segmenting genetic divergence data.