ABDUL-MALAK, DAVID
(2019)
Operations and Maintenance Optimization of Stochastic Systems: Three Essays.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
This dissertation presents three essays on topics related to optimally operating and maintaining systems that evolve randomly over time. Two primary areas are considered: (i) joint staffing and pricing strategies for call centers that use co-sourcing to improve service operations and reduce costs; and (ii) optimally maintaining stochastically degrading systems when either multiple systems are associated via a common environment, or when a single-unit system is maintained using a population of heterogeneous spare parts.
First we present a queueing and stochastic programming framework for optimally staffing a call center utilizing co-sourced service capacity. The interplay between the call center and external service provider is modeled as a leader-follower game in which the call center, acting as the follower, solves a two-stage stochastic integer program. The problem is reformulated as a quadratically-constrained linear program to obtain the optimal contract prices and the optimal staffing problem yields a closed-form solution. Numerically we demonstrate that significant cost reductions can be achieved, even in the presence of imperfect and asymmetric information. Second the problem of optimally replacing multiple stochastically degrading systems using condition-based maintenance is considered. Properties of the optimal value function and policy motivate a tractable, approximate model with state- and action-space transformations and a basis-function approximation of the action-value function. It is demonstrated that near optimal policies are attainable and significantly outperform heuristics. Finally, we consider the problem of optimally maintaining a stochastically degrading system using spares of varying quality. Conditions are provided under which the optimal value function exhibits monotonicity and the optimal policy is characterized. Numerically we demonstrate the utility of our proposed framework, and provide insights into the optimal policy as an exploration-exploitation type policy.
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Details
| Item Type: |
University of Pittsburgh ETD
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| Status: |
Unpublished |
| Creators/Authors: |
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| ETD Committee: |
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| Date: |
24 January 2019 |
| Date Type: |
Publication |
| Defense Date: |
14 November 2018 |
| Approval Date: |
24 January 2019 |
| Submission Date: |
19 November 2018 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
111 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Industrial Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
MAINTENANCE OPTIMIZATION
APPROXIMATE DYNAMIC PROGRAMMING
HETEROGENEOUS SPARE PARTS
CALL CENTER CO-SOURCING
MULTI-SYSTEM MAINTENANCE |
| Date Deposited: |
24 Jan 2019 16:22 |
| Last Modified: |
24 Jan 2019 16:22 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/35528 |
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