Time-based goal chasing method for mixed-model assembly line problem with multiple work stations

In sequencing problems for mixed-model assembly line in JIT production system, the Goal Chasing method (GC) is widely used for parts used leveling goal. The difference in assembly time of each product is not taken into consideration in the Goal Chasing method. Assembly time usually varies with product types. In recent years, the Time-Based Goal Chasing method (TBGC) has been proposed. The advantage of TBGC is to consider the influence of different assembly time of each product and idle time in production period. TBGC, however, has been only applied to single work station problems. In this paper, TBGC is applied to an assembly line problem with multiple work stations. Furthermore, the sequencing method and use of Simulated Annealing (SA) or Local Search (LS) for this problem are proposed.     

The mg-procedure in ranked set sampling

The MG-procedure in ranked set sampling is studied in this paper. It is shown that the MG-procedure with any selective probability matrix provides a more efficient estimator than the sample mean based on simple random sampling. The optimum selective probability matrix in the procedure is obtained and the estimator based on it is shown to be more efficient than that studied by Yanagawa and Shirahata [5]. The median-mean estimator, which is more efficient and could be easier to apply than that proposed by McIntyre [2] and Takahashi and Wakinoto [3], is proposed when the underlying distribution function belongs to a certain subfamily of symmetric distribution functions which includes the normal, logistic and double exponential distributions among others.     

The dynamic impacts of M&A on employment in Japan

This paper provides empirical evidence on the dynamic effects of merger and acquisition (M&A) on employment in Japan. The main contributions to the gaps in existing literature are: targeting employment effects of M&A, examining them by the deal type (merger and acquisition) and by the sector (manufacturing and non-manufacturing), tracing the effects in the long term, using large dataset with 9,880 sample firms and 2,530 M&A cases for the period from 1995 to 2008, and focusing on the case of Japan. Our main findings are: the “acquisition” with the key role of “extension and growth” proved to have positive effects in the dynamic terms on target firms’ employment, mainly in manufacturing sector with high labor productivity. On the other hand, the “merger” with key function of “consolidation” turned out to have negative impacts dynamically on post-merger firms’ employment, mainly in non-manufacturing sector with low labor productivity. The strategic implication might to be that the different employment responses to M&A events between manufacturing and non-manufacturing reflect the difference in labor productivity between them, i.e. the dual structure of Japanese economy.     

On mantel-haenszel type estimators in simple nested case-control studies

We are concerned with nested case-control studies in this article. For proportional hazards model, a class of over-all estimators of hazard ratios is presented when simple samples are drawn from risk sets. These estimators have the form of the Mantel-Haenszel estimator of odds ratio, and are consistent not only for large strata, but also for sparse data. Consistent estimators of the variances of the proposed hazard ratio estimators are also developed. An example is given to illustrate the proposed estimators.     

Estimating population characteristics by incorporating prior values in stratified random sampling/ranked set sampling

In this paper, we discuss the estimation of population characteristics using stratified random sampling in an infinite population framework, including ranked set sampling as a special case. The use of prior values is considered and the underlying distribution is assumed to be unknown. The estimator considered in each stratum is the weighted mean of the U-statistic and prior value. The optimum weight is obtained by minimizing the mean squared error of the estimator of the population characteristics, but it contains unknown parameters and those parameters are replaced with their estimates. Simulation results show the gains in efficiency of the proposed estimator, yielding gains of at least 1.2 times larger than the usual unbiased estimator under certain condition specified in the text. Guidelines for the usage of the proposed estimator are shown and an application to a real data set is provided.     

Mantel-Haenszel estimators for irregular sparse K2×J tables

This paper deals with sparse K2×J(J>2)$K2\times J(J>2)$ tables. Projection-method Mantel–Haenszel (MH) estimators of the common odds ratios have been proposed for K2×J$K2\times J$ tables, which include Greenland's generalized MH estimator as a special case. The method projects log-transformed MH estimators for all K2×2$K2\times 2$ subtables, which were called naive MH estimators, onto a linear space spanned by log odds ratios. However, for sparse tables it is often the case that naive MH estimators are unable to be computed. In this paper we introduce alternative naive MH estimators using a graph that represents K2×J$K2\times J$ tables, and apply the projection to these alternative estimators. The idea leads to infinitely many reasonable estimators and we propose a method to choose the optimal one by solving a quadratic optimization problem induced by the graph, where some graph-theoretic arguments play important roles to simplify the optimization problem. An illustration is given using data from a case–control study. A simulation study is also conducted, which indicates that the MH estimator tends to have a smaller mean squared error than the MH estimator previously suggested and the conditional maximum likelihood estimator for sparse tables.     

Characterization of probability models by an odds ratio in prospective and retrospective studies

It is shown that, when exposure variables are continuous, the odds ratios are functions of exposure differences if and only if Cox's binary logistic models hold in a prospective framework, and if and only if the underlying distribution belongs to a family of exponential type distributions in a retrospective framework.     

Incorporating historical controls using a random-effects model with a normal prior

Employing a variance stabilization transformation, a random-effects model with a normal prior is proposed for incorporating historical controls in the estimation of dose-response relationships. The advantages and disadvantages of maximum likelihood and empirical Bayes estimators are discussed. A two-stage method is introduced for the prudent use of historical controls.     

Estimating the Lyapunov exponent from chaotic time series with dynamic noise

In this paper, we propose an estimator of the Lyapunov exponent of the skeleton for chaotic time series with dynamic noise and prove the consistency of the estimator under some assumptions.     

Comparison of multiple behavioral traits between urban and rural squirrels

Urban Ecosystems - Recent rapid urbanization has imposed novel challenges to animals. Urban animals alter their behaviors such as increased boldness, exploration, and aggressiveness to cope with...