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We consider the problem of scheduling crash tests for new vehicle programs at Ford. We describe the development of a comprehensive web-based system that automates time-consuming scheduling analyses through mathematical optimization, while also institutionalizing expert knowledge about the engineering complexities of crash testing. We present a novel integer programming model and a corresponding solution algorithm that quickly generates efficient schedules. The system's user interface enables engineers to specify key program data and consider multiple scheduling scenarios, while using the underlying optimization model and solution algorithms as a black box. [ABSTRACT FROM AUTHOR]

The article discusses the use of an optimization approach to improve scheduling within robotic cells for FSI International Inc., a company that designs and manufactures robotic cells for wafer-fabrication companies. A robotic cell is a manufacturing system used in a variety of industries, including wafer fabrication. A wafer-fabrication cell contains several robot-served processing stations and produces identical wafers repetitively. Each wafer is processed through processing stations or stages as in a stage flow shop, and there are no buffers at or between the processing stations. Since a single type of wafer is produced, the optimal schedule is simply the sequence of robot moves that maximizes the throughput or, equivalently, minimizes the per-unit cycle time or the average time to produce a part in steady state. Since wafers are very valuable, even a small increase in throughput may lead to a substantial increase in profit. Consequently, throughput is a critical issue for the wafer-fabrication companies that are FSI's clients.

The article focuses on the application of operations research (OR) and management science (MS) to outside fields. In this climate of external cooperation, interactions, within the OR/MS area have received much less attention. Many papers are written every year testing one or more optimization algorithms on a few test problems; however, it is not sure how many of them are using any statistical analysis to extend and somehow generalize their algorithmic comparisons. The Optimization-Statistics relationship presents a two-way interaction: use of optimization procedures to solve statistical problems that are directly amenable to resolution by optimization techniques; and use of statistics in optimization. In the last five years, there have been two meetings that have addressed themselves to this area. Many individuals have been working in this interdisciplinary area, but there has been little interaction. Some coordination is needed via exchange of information, organization of formal meeting sessions and perhaps formulation of an interest group.

Moving military troops, which is critical to tactical success, depends on providing large quantities of fuel. We used simulation to model and analyze the Turkish army's fuel-supply system that consists of sea-going tankers, tank fields, pipelines, and depots. We measured performance of the existing and proposed systems under various scenarios. We developed a simulation optimization model based on a genetic algorithm (GA) to optimize system performance. Based on the results of extensive simulation experiments, we proposed a number of changes. We recommended that the army should open the existing fuel-supply system and that it establish commercial use in peacetime to obtain additional operating revenue. New trigger levels (or fuel-replenishment policies) for wartime allow the fuel-supply system to survive much longer even in the most severe war conditions. These specific recommendations are being considered by the top army officials to obtain benefits worth millions of dollars. [ABSTRACT FROM AUTHOR]

The article focuses on the use of decision simulator in implementing a dynamic programming approach to improve timber processing. Decision simulator permits user to test several crosscutting and log-allocating decisions for economic value. It allows the operator to inspect the stem before cutting and allocating it. Decisions for each stem are seen by the operator through logs and the profit contribution and also sees the stem cut and allocated through dynamic programming algorithm in order to increase profit contribution. He can repeatedly cut the same stem to search for alternative decisions.