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Group consensus is an important method for making business decisions. In this paper, the consensus process is defined as a dynamic and interactive group decision process, which is coordinated by a moderator who helps the experts to gradually move their opinions closer to each other. This paper describes the importance of group consensus and the need to minimize the cost of this process. Furthermore, this paper describes the costs associated with decision making using group consensus and then describes three methods of reaching consensus assuming quadratic costs for a single-criterion decision problem. The first method finds the group opinion (consensus) that yields the minimum cost of reaching throughout the group. The second method finds the opinion with the minimum cost of the consensus provided that all experts must be within a given distance of the group opinion. The last method finds the maximum number of experts that can fit within the consensus, given a specified budget constraint. Index Terms--Distributed decision making, group decision making, multiple experts.

For a simple finite graph G = (V, E) of order n, the optimal linear-arrangement problem seeks a vertex labeling f: V [right arrow] {1, 2, ..., n} for which the expression [[summation of].sub.({u,v})[member of]E]|f(u) - f(v)| is minimized. In this brief, we examine the following notion. Given some F G, is there a spanning tree of G having an optimal labeling that is also optimal for G? We specify some graph classes, which always exhibit these critical spanning trees and demonstrate how to construct them. Index Terms--Critical subgraph, graph theory, linear arrangement.

The effect of government borrowing on interest rates and consequently on private investment is discussed via a model based on the loanable funds theory. Conventional economic thinking expects interest rates to rise in response to borrowing and lead to a crowding-out effect on investment. However, later researches have weakened the validity of this hypothesis. Mixed results have been obtained at best.

THE IDEA OF DIETING AS AN OPERATIONS RESEARCH PROBLEM CAME TO ME WHILE TEACHING A LECTURE ON BOTTLENECKS. AT THE TIME I WAS IN MY MID-THIRTIES AND CLASSIFIED IN THE […]

This paper presents both approximate and exact merged knapsack cover inequalities, a class of cutting planes for knapsack and multiple knapsack integer programs. These inequalities combine the information from knapsack constraints and cover inequalities. Approximate merged knapsack cover inequalities can be generated through a O (n log ⁡ n) algorithm, where n is the number of variables. This class of inequalities can be strengthened to an exact version with a pseudo-polynomial time algorithm. Computational experiments demonstrate an average improvement of approximately 8 % in solution time and 5 % in the number of ticks from CPLEX when approximate merged knapsack cover inequalities are implemented as preprocessing cuts to solve some benchmark multiple knapsack problems. Furthermore, exact merged knapsack cover inequalities improve the solution time and number of ticks of some random multiple knapsack instances by 15 % and 5 % , respectively. [ABSTRACT FROM AUTHOR]

TODD EASTON [*] MARY C. KING [+] EASTON T. and KING M. C. (2000) Differences in wage levels among metropolitan areas: less-educated workers in the United States, Reg. Studies 34, [...]

The simplex method, created by George Dantzig, optimally solves a linear program by pivoting. Dantzig's pivots move from a basic feasible solution to a different basic feasible solution by exchanging exactly one basic variable with a nonbasic variable. This paper introduces the double pivot simplex method, which can transition between basic feasible solutions using two variables instead of one. Double pivots are performed by identifying the optimal basis in a two variable linear program using a new method called the slope algorithm. The slope algorithm is fast and allows an iteration of DPSM to have the same theoretical running time as an iteration of the simplex method. Computational experiments demonstrate that DPSM decreases the average number of pivots by approximately 41% on a small set of benchmark instances. [ABSTRACT FROM AUTHOR]

Baseball is an incredibly complex game in which the manager makes numerous difficult decisions. This paper describes a stochastic integer program that determines the best defensive starting positions to minimize the expected batting average of a particular player. To test this optimal defense against other standard Major League Baseball®defenses, a simulation is created. A computational study demonstrates how the optimal defense can be used to decrease Derek Jeter’s batting average in a statistically significant manner. [ABSTRACT FROM PUBLISHER]

This paper investigates the accuracy of six measures of housing cost differences among US metropolitan areas. Using Census data from 177 metropolitan areas, it tests the measures in two ways. First, it tests the ability of changes in the measures to predict changes in the shelter component of the metropolitan CPI from 1990 to 2000. Second, it tests the ability of the measures themselves to predict a proxy in 2000. A measure based on Fair Market Rents calculated by HUD placed second on the first test but did badly on the second. The housing component of the ACCRA index, a living cost measure frequently used by researchers, performed poorly on both tests. The top performer on both tests was a measure based on the average rent per room for a metropolitan area’s dwellings. Researchers wishing to control for living cost differences among places should consider including it in their living cost index. [ABSTRACT FROM AUTHOR]

ABSTRACT This research tests the ability of six metropolitan-level measures of housing costs to predict a benchmark housing cost measure based on Aten's area price level index. The first four measures are calculated with U.S. Census Data, the fifth is based on HUD Fair Market Rents, and the sixth is the housing portion of the ACCRA Index. In 25 large metropolitan areas, the fourth measure predicts 86 percent of the variation in the benchmark index in 1990 and 85 percent in 2000. The fifth measure performs nearly as well. The paper concludes both are promising measures of living costs. [ABSTRACT FROM AUTHOR]

Time of use (TOU) pricing is considered by many to be a key part of creating a more energy-efficient and renewable-energy-friendly grid. TOU pricing is also an integral part of the smart grid and is already available to customers of some electric utilities. With TOU pricing becoming a reality, intelligent dispatching systems that utilize energy storage devices (ESDs) to maximize the use of renewable resources, such as energy produced by small, customer owned wind generators and roof-top solar generators, and grid energy while determining the most economic dispatch schedule could play an important role for both the customer and the utility. The purpose of this work is to create an algorithm upon which these dispatching systems can be based. The details of one proposed algorithm are presented. Several case studies are presented to show the effectiveness of the algorithm from both a technical standpoint and an economic standpoint. The case studies show that while the algorithm developed is successful from a technical standpoint, the high cost of energy storage at this time limits its widespread deployment. [ABSTRACT FROM PUBLISHER]

Containing an epidemic at its origin is the most desirable mitigation. Epidemics have often originated in rural areas, with rural communities among the first affected. Disease dynamics in rural regions have received limited attention, and results of general studies cannot be directly applied since population densities and human mobility factors are very different in rural regions from those in cities. We create a network model of a rural community in Kansas, USA, by collecting data on the contact patterns and computing rates of contact among a sampled population. We model the impact of different mitigation strategies detecting closely connected groups of people and frequently visited locations. Within those groups and locations, we compare the effectiveness of random and targeted vaccinations using a Susceptible-Exposed-Infected-Recovered compartmental model on the contact network. Our simulations show that the targeted vaccinations of only 10% of the sampled population reduced the size of the epidemic by 34.5%. Additionally, if 10% of the population visiting one of the most popular locations is randomly vaccinated, the epidemic size is reduced by 19%. Our results suggest a new implementation of a highly effective strategy for targeted vaccinations through the use of popular locations in rural communities. [ABSTRACT FROM AUTHOR]

This work investigates determinants of metropolitan wage levels for workers with a high school education or less. It estimates their wage levels as a function of four factors: labor demand, industry mix, unionization, and the minimum wage. Labor demand and union strength influence wage levels most. The minimum wage and industry mix play smaller roles, although the minimum wage is the second most influential factor for men and women who did not complete high school. From 1990 to 1999, metropolitan wage levels exhibit considerable persistence, though persistence declines over this period. [ABSTRACT FROM AUTHOR]