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This teaching brief describes an engaging, in-class exercise that introduces genetic algorithms as well as advanced Excel functions and capabilities by modeling the familiar Sudoku puzzle. Student groups are first asked to manually solve a given puzzle and then translate that solution methodology to a spreadsheet model. This exercise can be used to build classroom community and as a launching point for the content area of genetic algorithms and the use of Evolutionary Solver.

To formulate a plan for affecting the future, business schools must first understand their origins as well as the multitude of current pressures and demands they face. The fundamental philosophy that drives business education, namely the maximization of shareholder wealth, must now be coupled with an emphasis on societal value creation. Liberal learning principles are vital for students to recognize their role in society, have a sense of purpose, develop human acumen and sound judgment, and hold a holistic perspective. Decision sciences educators are called upon to redesign their curricula to embed connections between business applications and liberal learning principles in decision sciences coursework itself.

Sudoku puzzles are both a source of entertainment for all ages and an algorithmic design challenge for mathematical modelers. Prior spreadsheet based optimization models for solving the Sudoku problem using Excel require the Premium Solver add-in, have complex constraint sets, and/or have limited success yielding solutions. This paper describes an alternate spreadsheet model formulation that uses relatively few decision variables, streamlined constraint sets, and can be solved using Evolutionary Solver which is included in the standard version of Excel. This approach for solving Sudoku problems is thus readily available for those involved in teaching and learning management science. [ABSTRACT FROM AUTHOR]

Supply chain management is a central and important area for academic research due to its impact on firms competing in today's global economy. Managing the flow of materials from supply sources to the ultimate customer represents a major challenge for today's managers. To assist managers, the concept of supply chain management has been adopted by many business leaders as an important way to assist in designing, planning, and controlling the network of facilities and tasks that comprise the many stages of the supply chain. In turn, the flow of academic research in the area has increased to provide a better set of guidelines for effective implementation and execution. This article sets the stage for recently completed research concentrating on supply chain management issues. First, a definition of supply chain management is provided and compared to recent usage in this area and logistics management. Also, a framework is provided that structures this dynamic and complex management task. Second, a review of past research is presented to illustrate the many paths supply chain management has traveled, and important contributions to supply management understanding and decision making. Third, recently completed research articles are introduced that have been selected to be part of this special issue of Decision Sciences. And fourth, future research directions for supply chain management that need to be pursued by interested investigators are discussed. [ABSTRACT FROM AUTHOR]