Linear programming models can help benchmark and monitor performance, based on various indicators, such as patient satisfaction, mortality rates, infection rates, and waiting times.

Balance multiple linear programming models effectively with these key strategies. Prioritize tasks, utilize automation tools, and adapt based on feedback for success.

This paper deals with a fuzzy goal programming methodology for solving multiobjective linear fractional chance constrained programming problems containing fuzzy numbers and exponentially distributed ...

This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform tasks, it is ...

According to Akpan [1], Linear programming (LP) can be used to find the best result for minimizing cost or maximizing profit for a real-life problem. This can be reached after converting this problem ...