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This essay introduces the IBM Optimization Subroutine Library (OSL) and seven OSL-related papers that appear in this issue. Developed as a result of a partnership between several IBM research and development groups, OSL provides a suite of tools for manipulating the models and solving the resulting minimization and maximization problems of mathematical optimization. The problems that OSL addresses include: linear, quadratic, mixed-integer, and pure network programming problems. OSL includes solvers based on the classical simplex method and on newer interior point methods. Because a user-supplied driver program coordinates the problem solution, and because of the “mix and match” philosophy of OSL, a user may, within rather wide limits, individually tailor a technique to solve a particular problem. We conclude that OSL is something new in optimization software.
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