Three essays on algorithmic approaches for operations management


Foroughi, Amir


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URN: urn:nbn:de:bsz:180-madoc-640978
Dokumenttyp: Dissertation
Erscheinungsjahr: 2023
Ort der Veröffentlichung: Mannheim
Hochschule: Universität Mannheim
Gutachter: Stolletz, Raik
Datum der mündl. Prüfung: 8 Juli 2022
Sprache der Veröffentlichung: Englisch
Einrichtung: Fakultät für Betriebswirtschaftslehre > ABWL u. Produktion (Stolletz 2010-)
Lizenz: CC BY 4.0 Creative Commons Namensnennung 4.0 International (CC BY 4.0)
Fachgebiet: 650 Management
Freie Schlagwörter (Englisch): outpatient appointment scheduling , simulation optimization , multifidelity simulation , routing , warehousing , product location , time-dependent queues with overloading
Abstract: Operations management is an area of business concerned with producing goods and services. It manages the conversion of inputs (such as materials, labor, and energy) into outputs (in goods and services). It ensures that business operations are efficient in using as few resources as required and effective in meeting consumer needs. Operations management is responsible for a wide range of decisions, such as planning capacity for manufacturing plants, designing the structure of supply chain networks, and developing and operating service systems. Decision-making in operations management is often reinforced by analytical and algorithmic tools which are based on logic and consider all available data and possible alternatives. This dissertation focuses on designing different algorithmic approaches supporting decision-making in operations management. It consists of three articles that design, implement, and analyze one or several algorithms for distinct practical problems in operations management. The papers are coauthored by Professor Dr. Schneider, Professor Dr. Emde, Professor Dr. Boysen, and Professor Dr. Stolletz. Each article describes the potential motivation of the research, positioning in the literature, and a detailed problem/model description. In addition, numerical results of each, generate insights into problems described in every chapter.




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