Genetic Algorithm vs Expert System

Question

I'm having some doubts about which system should I use for a new software.
No code has been written yet, I'm just breaking apart all the needs and only then start coding.
This will be implemented in a computer company that provides services for other companies, onsite and remotely.
These are my variables:

• Number of technicians
  
• Location of customer
  
• Type of problem
  
• Services already scheduled for the technician
  
• Expertise of the technician about the situation
  
• Customer priority

Maybe some are missing, but these are the most important ones.
This job is being done manually, and has humans, we fail to see the best route to be taken sometimes.
Let's say that a customer calls with a printer problem.
First, check which tech knows about printers.
Then, is the tech available? far from the customer? can it be done remotely (software issues)?
Can it be done by another tech who is closer from the customer location?
Does this customer have more priority than the other where the same tech should be going?
Is the technician schedule full? If yes, pass to another printer/hardware tech.

I know my english is not perfect (not my natural language), but I'll try to provide more details or correct the text as needed.

So, my question is this, what kind of approach would you take? Genetic algorithm seems nice for this kind of job, and I also have some experience with GAF and WatchMaker (Java GA Framework). However, when reading the text above, an expert system seems also appropriate.
Have someone done something like this?!
I had search for this kind of software and couldn't find anything alike.
Would another approach be better than the two asked?!
Also, I'm building up a table with all the techs capabilities and expertise, with simple rules like, 1 to 5 about each expertise. This is also a decision factor.
Thanks.

Answer 1

Why not do both? Use an expert system (a rule engine) to define your constraints and use a metaheuristic (such as Local Search or Genetic Algorithms) to solve it. The planning engine OptaPlanner (java, open source) does exactly that (by using the rule engine Drools). The architecture look likes this:

Here's a video demonstrating the constraint flexibility on the vehicle routing problem (VRP). Your problem seems to be an advanced variant on VRP (which is a variant on TSP).

Answer 2

Maybe you can start off with TSP, here http://en.m.wikipedia.org/wiki/Travelling_salesman_problem

I guess it only deals with the distance.