This work aims to solve the optimization problem associated with the allocation of laboratory samples in plates. The processing of each of these plates is costly both in time and money, therefore the main objective is to minimize the number of plates used. The characteristics of the problem are reminiscent of the well-known bin packing problem, an NP-Hard problem that, although it is feasible to model as a linear programming problem, it cannot be solved at a reasonable cost. This work, proposes the implementation of a heuristic algorithm that provides good results at a low computational cost.

No abstract

This work focuses on the study of a task planning problem in a home care business. The objective is to schedule the working days of the available nurses, in order to assist all the active clients. Due to the large size of the real cases that must be faced, it is not possible to obtain exact solutions of the problem in short periods of time. Therefore, we propose an algorithm, which is based on heuristic techniques, to provide approximated solutions to the incidents that arise daily in the company. The designed algorithm is validated by obtaining the automatic schedule to solve a battery of real-like examples.