Finding Improving Solutions that Control Disruption to Binary Optimization Problems Public
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Conventional optimization solvers provide a single optimal solution to an optimization model, which in some cases is undesirable to the decision maker because of the large discrepancy between the optimal solution and the existing conditions of the real-world situation the model represents. This project focuses on developing an algorithm and computational program to generate solutions to binary integer optimization problems that can simultaneously improve the objective function value and yet control disruption from the current condition. The program uses Dinkelbach’s algorithm to determine such a solution, and is implemented in Excel utilizing Visual Basic for Applications (VBA) in conjunction with OpenSolver. Detailed instructions are included to guide users through the entire process.
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Permanent link to this page: https://digital.wpi.edu/show/w0892c50s