Solution procedure for a repair-limit problem using the TTT concept

We address the problem of controlling the repair-time limitof a one-unit repairable system in order to minimize the totalexpected cost for one cycle, when repair time is random. Theunderlying theoretical problem is reduced to the geometricalone using the TTT concept. We obtain the optimal repair-limitpolicy analytically/graphically and show that the optimal solutionis calculated simply from the complete data of repair time withoutspecifying the distribution function. We also develop computersoftward to obtain the optimal repair-limit policy numerically,and illustrate its use by examples.     

Chalk it up to experience: using chalkboard paint to create mathematical manipulatives

In this article, we give two examples of creating portable chalkboards using chalkboard paint for students to use during cooperative learning. This provides a creative method for professors to facilitate active learning in the undergraduate mathematics classroom.     

Designing examples to create variation patterns in teaching

This paper uses a post-qualitative philosophical perspective to find new ways of understanding teaching and learning. The paper presents a series of examples that were used in a longitudinal study, with the aim of creating variation patterns that would make it possible for students to discern the use of the four basic arithmetic operations in different situations. The focus of this article is the potential of the examples to systematically create variation patterns that students need to perceive in order to make generalizations. The result demonstrates that well-thought-out examples help identify the correct arithmetic operation in different situations, and provide a basis from which students can discern the connection between text and the use of operation in mathematical example. The result also demonstrates that students develop rhizomatic thinking through the creation of new links between aspects of the object of learning, association and linking of different aspects to each other and the creation of a whole with unique and specific characteristics that cannot be explained by simply adding the characteristics of the individual parts.     

A methodology to create robust job rotation schedules

This research proposes a methodology for developing robust job rotation schedules to reduce the likelihood of low back injury due to lifting. We consider settings that have uncertain task demands and different worker profiles in order to simulate real settings. We begin by considering deterministic versions of the problem and solve these using mathematical programming. Because mathematical programming cannot be readily applied to stochastic versions of the problem, heuristic solution methods are developed. The effectiveness of these methods is demonstrated by comparing the results with provably optimal solutions from the deterministic problems and with an enumerative approach that is applied to the stochastic version of the problem. Across the test problems, the proposed heuristics are effective at finding good job rotation solutions. The proposed methods could also be applied to solve other job rotation objectives such as maximizing productivity and reducing exposure to other work environmental factors such as excessive noise.     

Dot plots and hat plots: supporting young students emerging understandings of distribution,center and variability through modeling

An important use of statistical models and modeling in education stems from the potential to involve students more deeply with conceptions of distribution, variation and center. As models are key to statistical thinking, introducing students to modeling early in their schooling will likely support the statistical thinking that underpins later, more advanced work with increasingly sophisticated statistical models. In this case study, a class of 10–11 year-old students are engaged in an authentic task designed to elicit modeling. Multiple data sources were used to develop insights into student learning: lesson videotape, work samples and field notes. Through the use of dot plots and hat plots as data models, students made comparisons of the data sets, articulated the sources of variability in the data, sought to minimize the variability, and then used their models to both address the initial problem and to justify the effectiveness of their attempts to reduce induced variation. This research has implications for statistics curriculum in the early formal years of schooling.     

Detecting tail behavior: mean excess plots with confidence bounds

In many practical situations exploratory plots are helpful in understanding tail behavior of sample data. The Mean Excess plot is one of the exploratory tools often used in practice to understand the right tail behavior of a data set. It is known that if the underlying distribution of a data sample is in the maximum domain of attraction of a Fréchet, a Gumbel or a Weibull distributions then the ME plot of the data approaches a straight line in an appropriate sense, with positive, zero or negative slope respectively. In this paper we construct confidence intervals around the ME plots which assist us in ascertaining which particular maximum domain of attraction the data set comes from. We recall weak limit results for the Fréchet domain of attraction, already obtained in Das and Ghosh (Bernoulli 19, 308–342 2013) and derive weak limits for the Gumbel and Weibull domains in order to construct confidence bounds. We demonstrate our methodology by applying them to simulated and real data sets.     

Information support system for a program to select a minimum linear basis

Translated from Aktual'nye Voprosy Prikladnoi Matematiki, pp. 32–36, 1989.     

Utilizing the IP Multimedia Subsystem to create an extensible service-oriented architecture

Smart Spaces provide very promising means of creating context-aware environments. Unfortunately, a lack of information about users within Smart Spaces limits their usefulness. We propose a novel solution that involves integrating Smart Spaces with social networks through the IP Multimedia Subsystem. to create truly context-aware and adaptive spaces. By utilizing the wealth of user information present within social networks, smarter and more adaptive spaces can be created. We therefore propose the design and implementation of “SocioSpace” a Smart Spaces framework that utilizes the social context. We design and implement all components of SocioSpace, including the central server, the location management system, social network interfacing components, service delivery server and user agents. We then run various scenarios to test the reliability of the system. The results show the effectiveness of our framework in successfully creating Smart Spaces that can truly utilize social networks to deliver adaptive services that enhance the users’ experiences and make the environment more beneficial to them.     

Rounding to an integral program

This paper presents a framework for approximating NP-hard problems that can be formulated as integer-covering programs, possibly with additional side constraints, and the number of covering options is restricted in some sense, although this property may be well hidden.     

The fleet assignment problem: Solving a large-scale integer program

Given a flight schedule and set of aircraft, the fleet assignment problem is to determine which type of aircraft should fly each flight segment. This paper describes a basic daily, domestic fleet assignment problem and then presents chronologically the steps taken to solve it efficiently. Our model of the fleet assignment problem is a large multi-commodity flow problem with side constraints defined on a time-expanded network. These problems are often severely degenerate, which leads to poor performance of standard linear programming techniques. Also, the large number of integer variables can make finding optimal integer solutions difficult and time-consuming. The methods used to attack this problem include an interior-point algorithm, dual steepest edge simplex, cost perturbation, model aggregation, branching on set-partitioning constraints and prioritizing the order of branching. The computational results show that the algorithm finds solutions with a maximum optimality gap of 0.02% and is more than two orders of magnitude faster than using default options of a standard LP-based branch-and-bound code.This work was supported by NSF and AFORS grant DDM-9115768 and NSF grant SES-9122674.Corresponding author.     

The value function of a mixed integer program: II

We prove that the gap in optimal value, between a mixed-integer program in rationals and its corresponding linear programming relaxation, is bounded as the right-hand-side is varied. In addition, a variant of value iteration is shown to construct subadditive functions which resolve a pure-integer program when no dual degeneracy occurs. These subadditive functions provide solutions to subadditive dual programs for integer programs which are given here, and for which the values of primal and dual problems are equal.     

Verification of a program complex

For verification of a complex of programs interacting in a complicated way, the programs can be described asprocesses in astate space. Properties to be verified can be expressed in a similar manner. In this paper such a method is applied to the restart facility of an online database system.     

AN EXTENSION OF PREDICTOR-CORRECTOR ALGORITHM TO A CLASS OF CONVEX SEPARABLE PROGRAM

1.IntroductionIn[1]Mizuno,ToddandYepresentedapredictor-correctoralgorithmforlinearpramgrammingwhichpossessesaquadraticconvergencerateofthedualgaptozero.GuoandWul6]gaveamodificationofthisalgorithmforsolvingconvexquadraticprogramwithupperbounds.Itisshownthatthemodifiedmethodnotonlypreservesalltheoriginalmerits,butalsoreducesthedualgapbyaconstantfactorineachcorrectorstep,incontrasttotheMizuno,TOddandYe'soriginalpredictor--correctormethodwherethedualgapremainsunchanged.Thealgorithmdiscussedint…     

A note on treating a second order cone program as a special case of a semidefinite program

It is well known that a vector is in a second order cone if and only if its arrow matrix is positive semidefinite. But much less well-known is about the relation between a second order cone program (SOCP) and its corresponding semidefinite program (SDP). The correspondence between the dual problem of SOCP and SDP is quite direct and the correspondence between the primal problems is much more complicated. Given a SDP primal optimal solution which is not necessarily arrow-shaped, we can construct a SOCP primal optimal solution. The mapping from the primal optimal solution of SDP to the primal optimal solution of SOCP can be shown to be unique. Conversely, given a SOCP primal optimal solution, we can construct a SDP primal optimal solution which is not an arrow matrix. Indeed, in general no primal optimal solutions of the SOCP-related SDP can be an arrow matrix.Mathematics Subject Classification (2000): 20E28, 20G40, 20C20     

An introduction to the Ribe program

We survey problems, results, ideas, and recent progress in the Ribe program. The goal of this research program, which is motivated by a classical rigidity theorem of Martin Ribe, is to obtain structural results for metric spaces that are inspired by the local theory of Banach spaces. We also present examples of applications of the Ribe program to several areas, including group theory, theoretical computer science, and probability theory.