In this paper, we give an up-to-date overview of how important ideas from optimization, probability theory and multicriteria decision analysis are interwoven to address situations where the presence ...

3. Methodology The framework developed for this approach uses a mixed-integer linear programming formulation, balancing imprecision from linearization with benefits of global optima and rapid ...

Linear programming has broad applications across various disciplines, including mathematics, as well as in fields like economics, business, telecommunications, and manufacturing. In this discussion, ...

In our project, "Mathematical Linear Optimization with R for Support Staffing at Tesla in the Heart of Silicon Valley," we addressed the critical challenge of optimizing staffing schedules while ...

3. An Illustrative Example In order to illustrate the method based on linear programming, we consider an example with 15 jobs and 11 production cells and the mathematical model for 15 types and 11 ...

In this paper, we consider a Fuzzy Stochastic Linear Fractional Programming problem (FSLFP). In this problem, the coefficients and scalars in the objective func ...