Data mining is proving to be a valuable tool, by identifying potentially useful information from the large amounts of data collected, and enabling an organization to gain an advantage over its competitors. This article defines what data mining is and covers the operations of data mining as have been classified throughout literature. It then focuses on the important uses of data mining, which include but are not limited to marketing, risk management, fraud detection, and customer acquisition and retention. Examples of how the banking and retail industries have been effectively utilizing data mining in these areas are provided.

This paper proposes four new very powerful heuristics which utilize a two-phase method to obtain multi-period facility location solutions. The logic of these heuristics was based on existing methods. In the first phase, single-period solutions were generated. In the second phase, dynamic programming was used to solve for the best available sequence of facility configurations over the entire planning horizon.Extensive computational results were presented that compare the heuristic solutions to those of the optimum under varying conditions such as different demand patterns, time periods, cost structure, and number of facilities. The computational results of the heuristics were extremely favorable.

An exact and three approximate solution methods for the two-commodity location problem (TCLP) are presented and tested in this paper. The exact solution integrates mixed integer programming and dynamic programming methods.First, a mixed integer programming approach is used to generate a minimum number of solutions with respect to each commodity. Second, commodities are treated as stages of a dynamic environment and dynamic programming is employed to find the optimal assignment of commodities to facilities. This integrated solution methodology is an effective technique. It provides many near-optimal solutions that may be used for post-optimality analysis. An illustrative example is provided.

Engineering changes (EC) constitute a normal part of a product's life cycle. However, engineering change management has been a neglected area in the field of operations management. The purpose of this research is to introduce the necessary steps for the implementation of an effective engineering change management (ECM) system. The ECM system outlined here consists of five phases: (I) engineering change request, (2) information gathering and analysis, (3) change authorization board evaluation and approval, (4) engineering change implementation, and (5) follow-up. The optimum approach is to determine the "root cause" of the changes, and to reduce the number of changes.

The United States has been losing its manufacturing base because of severe international competition. One way to help improve the US economy is to revitalize its manufacturing sector. Training workers and equipping managers with the necessary tools and competencies to help organizations improve production and operations will be vital in this effort. We conducted a study with two purposes: (1) to obtain a list of required and elective courses in operations management (OM) and industrial management (IDM) programs offered by US universities at the undergraduate level, and (2) to rank these courses in order of importance in different programs and for five proposed concentrations.

An exact algorithm for the multi-period facility location problem is proposed that efficiently integrates mixed-integer and dynamic programming methods. Two simplification procedures are introduced to reduce the size of the general multi-period facility location problem substantially. Because the proposed algorithm utilizes dynamic programming to obtain the optimal sequence over the entire planning horizon, many near-optimal solutions also become available that are extremely useful for postoptimality analysis. The solution method is tested and compared with a well-known procedure on several problems with varying conditions. The comparisons appear very promising, and the required CPU times by the proposed method are substantially reduced.