Solving Generalized Networks

Article Abstract:

A complete, unified description is given of the design, implementation and use of a family of very fast and efficient large-scale minimum-cost (primal simplex) network programs. The class of capacitated generalized transshipment problems solved includes the capacitated and uncapacitated generalized transportation problems and the continuous generalized assignment problem, as well as the pure network flow models which are specializations of these problems. These formulations are used for a large number of diverse applications to determine how (or at what rate) flows through the arcs of a network can minimize total shipment costs. A generalized network problem can also be viewed as a linear program with at most two nonzero entries in each column of the constraint matrix; this property is exploited in the mathematical presentation with special emphasis on data structures for basis representation, basis manipulation, and pricing mechanisms. A literature review accompanies computational testing of promising ideas, and extensive experimentation is reported which has produced GENNET, an extremely efficient family of generalized network systems. (Reprinted by Permission of Publisher.)

Algorithms, Transportation, Mathematical software, Algorithm, Statistical software, Simplexes (Mathematics), Evaluation, Network Models, Statistical/Mathematical Software, Mathematical Programming, Routing, Simplex Method, Matrix Computations

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The road to "root cause": shop-floor problem-solving at three auto assembly plants

Article Abstract:

Problem-solving processes at three North American automobile assembly plants are compared. Focus is on in-plant problems related to production that impact quality but which cannot be attributed to a single, clear source. Three problem categories in particular that require collaborative problem-solving and which are quantified in J.D. Power consumer surveys are investigated, namely, water leaks, paint defects and functional electrical defects. Fieldwork focuses on the initial three stages of the problem-solving process, patterned after a common model that includes problem definition, problem analysis, generation and selection of solutions, testing and evaluation of solutions and routinization. Problem-solving is found to benefit from rich data that offer multiple perspectives on a problem and provide information in the problem's physical context.

Methods, Management, Problem solving, Factory management, Automobile factories, Automotive factories

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Financial data and the skewed generalized t distribution

Article Abstract:

A study was conducted to determine a skewed extension of the generalized t distribution developed by J.B. McDonald and W.K. Newey in 1988. It is a flexible distribution supporting the skewness and excess kurtosis present in financial data. The mathematical moments and other characteristics of the distribution were determined. The Maximum Likelihood estimators of the parameters of the distribution were then obtained from the optimization of the sample log-likelihood function. Six applications of the distribution to financial data were carried out to show excess kurtosis and skewness. Results indicated that the skewed generalized t distribution supported a very good fit to the empirical distribution of data.

Analysis, Distributions, Theory of (Functional analysis), Theory of distributions, Functions, Exponential, Exponential functions, Laplace transformation

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