University of Twente Student Theses
Assignment of Inspection Visits to Customers with Different Urgencies
Zeraïria, Amalie (2023) Assignment of Inspection Visits to Customers with Different Urgencies.
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| Abstract: | We are dealing with a company employing damage experts. The company has contracts with several insurance companies, and a damage expert must visit the client when they submit a damage declaration. The clients have different urgencies (SLA) and when a client calls with a visit request, the planner of the company assigns the client to a certain day and time slot, not earlier than tomorrow. When to schedule a client is based on the company’s policy. In this paper an answer to the following research question will be formulated: "Can we find a(n optimal) policy that outperforms the already existing policies and considers the SLA, the load of the upcoming day(s), and the previous assignments of visits to days and their geographical spread?". In order to answer this question, first the problem is mathematically formulated as a Markov Decision Process(MDP). Once formulated, an optimal policy is found using dynamical programming. This optimal policy has been compared with an already existing policy and performs better on some aspects. This is computationally really complex, since the number of possible states is a gigantic number. So an optimal policy is found for a small example. To get more realistic results, the simulation program from the company P.C.A. B.V. is used to implement a new, self-invented policy based on a waiting list and to compare the results with already existing policies. This self-invented policy outperforms the other policies in a lot of perspectives. However whether this is the best for a company and its clients, is a question for them to answer. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 31 mathematics |
| Programme: | Applied Mathematics BSc (56965) |
| Link to this item: | https://purl.utwente.nl/essays/96730 |
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