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Over the years, most of the firms have focused their attention to the effectiveness and efficiency of separate business functions. As a new way of doing business, however, a growing number of firms have begun to realize the strategic importance of planning, controlling, and designing a supply chain as a whole. In an effort to help firms capture the synergy of inter-functional and inter-organizational integration and coordination across the supply chain and to subsequently make better supply chain decisions, this paper synthesizes past supply chain modeling efforts and identifies key challenges and opportunities associated with supply chain modeling. We also provide various guidelines for the successful development and implementation of supply chain models.

Introduction to Optimization taught by Cliff Ragsdale Aim of Course: Scarcity is a dominant feature of the economic landscape - time, labor and other inputs into business processes.  The essence of management is to make choices that make optimal use of scarce resources. Students in this course will learn how to apply linear programming to complex systems to make better decisions - decisions that increase revenue, decrease costs, or improve efficiency of operation.   The course introduces the role of mathematical models in decision-making, then covers how to formulate basic linear programming models for decision problems where multiple decision need to be made in the best possible way, while simultaneously satisfying a number of logical conditions (or constraints).  Students will use spreadsheet software to implement and solve these linear programming problems. Course Program: SESSION 1: Introduction The role of models in decisions Sources of bias & error in human decision making Good decisions vs. good outcomes SESSION 2: Linear Programming Models Formulating linear programming models Graphical representations Solving LP models in spreadsheets SESSION 3: Domain Specific Illustrations Make or buy Investment Transportation Blending SESSION 4: Sensitivity Analysis Role of sensitivity analysis in the larger decision context Shadow prices Alternate solutions Robust Optimization Simplex Method HOMEWORK: Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.