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Stochastic Linear Programming

Planning under uncertainty

Professors George Dantzig and Gerd Infanger have a special interest in developing methods and software for stochastic linear programming.

This SOL research program concerns techniques for solving mathematical models of decision problems whose parameters (coefficients, right-hand sides) are not known with certainty but are assumed known from their distributions. Such models arise in all practical problems of planning, scheduling, designing, and controlling complex situations. The models are extremely large. New breakthrough methods, based on sampling, now make them solvable. Our activities include fundamental theoretical research on algorithms for stochastic linear and nonlinear programs, efficient software implementations on serial and parallel computers, and applications research in diverse areas. Recent applications include: planning, scheduling, and control of electric power systems; design and operation of production lines; portfolio optimization and asset-lifability management; vehicle placement and scheduling in transportation, optimal design of communication systems.