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In this project, we want to investigate if deep learning methods can contribute in combinatorial optimization problems in particular if it can find any pattern among good solutions for a pickup and delivery problem and if so, then take advantage of it to lead the search toward even better solutions. INF is highly recommended. Develop a Machine Learning based Hyper-heuristic algorithm to solve a pickup and delivery problem. A hyper-heuristic is a heuristics that choose heuristics automatically.
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Master of Science in Applied Economics and Management

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Master of Science (MS) in Applied Economics and Management | Cornell Dyson

Linear Programming: Modeling Examples 1. Betty Malloy, owner of the Eagle Tavern in Pittsburgh, is preparing for Super Bowl Sunday, and she must determine how much beer to stock. Betty stocks three brands of beer- Yodel, Shotz, and Rainwater. Based on past football games, Betty has determined the maximum customer demand to be gallons of Yodel, gallons of shotz, and gallons of Rainwater.
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Dantzig—Wolfe decomposition is an algorithm for solving linear programming problems with special structure. It was originally developed by George Dantzig and Philip Wolfe and initially published in Dantzig—Wolfe decomposition relies on delayed column generation for improving the tractability of large-scale linear programs. For most linear programs solved via the revised simplex algorithm , at each step, most columns variables are not in the basis. In such a scheme, a master problem containing at least the currently active columns the basis uses a subproblem or subproblems to generate columns for entry into the basis such that their inclusion improves the objective function.
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