In this study, we propose an exact method for optimizing a linear function over the efficient set of a multi-objective transportation problem (MOTP). This type of problem arises when a decision maker ...

Industrial organizations are racing to implement AI, yet many struggle to demonstrate concrete value from their investments. The missing element isn't better algorithms or more data; it's clarity ...

O.A.Pavlov,M.Y.Kyselov,B.P.Palekha, AGGREGATED VOLUMETRIC-TEMPORARY PLANNING MODELS FOR ONE CLASS OF DISCREET PRODUCTION SYSTEMS. Optimization of schedules for discrete production systems with time ...

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

Blood tests and “biodata” have entered the fitness space. By Dana G. Smith On Monday, the high-end gym chain Equinox introduced a longevity program with a $40,000 annual membership fee. According to a ...

Abstract: This paper deals with the multi-objective chance constrained programming, where the right hand side of the constraints are normally distributed and the objective functions with fuzzy numbers ...

I try to apply the model for solving my MILP problem. There are four power generation units: GT, U2, U3, U4, each has a minimum and maximum power Pmin and Pmax. Each unit has a cost-generating linear ...

Abstract: The conventional Linear Programming (LP) model requires the parameters to be known as constants. In the real world, however, the parameters are seldom known exactly and have to be estimated.