Applications of Resource-Constrained Project Scheduling in Service Operations Management

Zimmermann, Adrian (2016). Applications of Resource-Constrained Project Scheduling in Service Operations Management. (Dissertation, Universität Bern, Wirtschafts- und Sozialwissenschaftliche Fakultät)

[img]
Preview
Text
16zimmermann_a.pdf - Published Version
Available under License Creative Commons: Attribution-Noncommercial-No Derivative Works (CC-BY-NC-ND).

Download (881kB) | Preview

Service companies employ expensive personnel to provide services for their customers. Each service may involve a large number of individual activities that must be executed by the company's personnel. Furthermore, the customers often pay for the services provided once all these activities have been completed. Hence, in general, managers plan the service operations of their companies such that the time required to complete each service is minimized, i.e., the available personnel is utilized in the most efficient way. In this dissertation, we consider two complex planning problems that arise in service operations management: the short-term planning of assessment centers and the scheduling of projects with so-called work-content constraints. Both planning problems consist of a prescribed number of activities that must be executed by the available personnel such that the duration of the service, i.e., the duration of the assessment or the project, is minimized. We interpret these two planning problems as specific applications of the well-known resource-constrained project scheduling problem, and we devise novel solution approaches for the planning problems that are based on concepts and methods from the corresponding project-scheduling literature. For the short-term planning of assessment centers, we devise a multi-pass list-scheduling heuristic and five alternative mixed-integer linear programming formulations. For the scheduling of projects with work-content constraints, we develop a mixed-integer programming-based heuristic. Our computational results indicate that the proposed approaches obtain optimal or near-optimal solutions for the two respective planning problems in a short amount of computation time.

Item Type:

Thesis (Dissertation)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Financial Management > Professorship for Quantitative Methods in Business Administration

UniBE Contributor:

Zimmermann, Adrian, Trautmann, Norbert

Subjects:

600 Technology > 650 Management & public relations

Language:

English

Submitter:

Igor Peter Hammer

Date Deposited:

23 Jan 2018 09:21

Last Modified:

05 Dec 2022 15:09

URN:

urn:nbn:ch:bel-bes-3117

Additional Information:

e-Dissertation (edbe)

BORIS DOI:

10.7892/boris.109716

URI:

https://boris.unibe.ch/id/eprint/109716

Actions (login required)

Edit item Edit item
Provide Feedback