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Niv Buchbinder, Kamal Jain, Mohit Singh, Secretary Problems via Linear Programming, Mathematics of Operations Research, Vol. 39, No. 1 (February 2014), pp. 190-206 ...

Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear Programming: regression, classification and other engineering applications. Integer Linear Programming: Basics, ...

NVIDIA's cuOpt leverages GPU technology to drastically accelerate linear programming, achieving performance up to 5,000 times faster than traditional CPU-based solutions.

For linear optimization problems, the optimum is found in an extremal point. But this is not the case for non-linear problems. Consider a critical issue for many academics: the life-work balance. We ...

Bounds and approximate formulae are developed for the average optimum distance of the transportation linear programming (TLP) problem with homogeneously, but randomly distributed points and demands in ...

Solve linear optimization problems including minimization and maximization with simplex algorithm. Uses the Big M method to solve problems with larger equal constraints in Python ...

In this research, focusing on two-level linear programming problems involving fuzzy random variables, we pro pose a new decision making model through possibility measures. Taking into account ...

Karmarkar (1984) found the first method of the interior point algorithm, so linear programming appeared as a dynamic field of research. Soon after, the interior point algorithm was able to resolve ...

We identify the effects of multi-dimensional queries to specify the target set in the influence maximization problem, and propose the formal problem definition of Multidimensional Selection based ...