  The social worker scheduling problem is a class of combinatorial optimization
problems that combines scheduling with routing issues. These types of problems
with classical computing can only be solved, in the best of cases, in an
approximate way and significantly when the input data does not grow
considerably. Today, the focus on the quantum computer should no longer be only
on its enormous computing power, but also on the use of its imperfection for
this era, (Noisy Intermediate-Scale Quantum (NISQ)) to create a powerful
optimization and learning device that uses variational techniques. We had
already proposed a formulation and solution of this problem using the capacity
of the quantum computer. In this article, we present some broad results of the
experimentation techniques. And above all, we propose an adaptive and
intelligence solution, which efficiently recalculates the schedules of social
workers. Taking into account new restrictions and changes in the initial
conditions, by using a case-based reasoning system and the variational quantum
eigensolver based on a finite-depth quantum circuit. That encodes the ground
state of the Hamiltonian of social workers.
  The quantum feasibility of the algorithm will be modelled with docplex and
tested on IBMQ computers.
