A METHOD FOR SOLVING LINEAR PROGRAMS WITH VARIABLE RESOURCES

This paper is concerned with the solution of linear and linear goal programming problems in which the values of the right-hand side parameters are not fixed constants. Specifically, we are concerned with linear optimization problems in which the right-hand sides of the constraining equations are free to vary subject to a set of linear constraining equations. By formulating a relaxed linear program wherein the right-hand sides are treated as variables, we show how it is possible to solve one larger linear program that yields as a solution not only the optimal values for the decision variables, but also the optimal values for the right-hand sides.     

THE DEVELOPMENT OF AN INTEGRATIVE CURRICULUM IN AN UNDERGRADUATE BUSINESS PROGRAM*

This paper describes how the core portion of the undergraduate business program at Indiana University was revised to facilitate integration of basic functionally oriented decision making skills and thus help students gain a deeper understanding of the interdependence of business decisions. It relates, in essence, why and how a single computer-oriented case study which demanded a solution to a large-scale, unified finance-marketing-production problem was used at Indiana University, mentions how we plan to accomplish further integration of functional material, and provides some insight into student reaction to what was, in fact, a massive project from both student and administrative points of view.     

OPTIMIZING UNIVERSITY ADMISSIONS PLANNING

The crucial issues in the administration of higher education embody the very purpose, function, and concept of each institution. The institution's administrative policies are based on the combined philosophy of many conflicting interest groups such as taxpayers, donors, administrators, faculty, students, staff, and users of university services. A function performed by the university which is receiving increasing attention and outside pressure is the formulation of admissions policy for newly entering students. This paper investigates problems involved in the admissions planning and presents a goal programming model as an optimization tool for the problem.     

A new heteroscedastic regression to analyze mass loss of wood in civil construction in Brazil

A heteroscedastic regression based on the odd log-logistic Marshall–Olkin normal (OLLMON) distribution is defined by extending previous models. Some structural properties of this distribution are presented. The estimation of the parameters is addressed by maximum likelihood. For different parameter settings, sample sizes and some scenarios, various simulations investigate the performance of the heteroscedastic OLLMON regression. We use residual analysis to detect influential observations and to check the model assumptions. The new regression explains the mass loss of different wood species in civil construction in Brazil.