Polynomial Time Algorithms for Some Multi-Level Lot-Sizing Problems with Production Capacities

Arbeitspapier

We consider a model for a serial supply chain in which production, inventory, and transportation decisions are integrated, in the presence of production capacities and for different transportation cost functions. The model we study is a generalization of the traditional single-item economic lot-sizing model, adding stationary production capacities at the manufacturer, as well as multiple intermediate storage levels (including the retailer level), and transportation between these levels. Allowing for general concave production costs and linear holding costs, we provide polynomial time algorithms for the cases where the transportation costs are either linear, or are concave with a fixed-charge structure. In the latter case, we make the additional common and reasonable assumption that the variable transportation and inventory costs are such that holding inventories at higher levels in the supply chain is more attractive from a variable cost perspective. The running times of the algorithms are remarkably insensitive to the number of levels in the supply chain.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Tinbergen Institute Discussion Paper ; No. 02-066/4

Classification and Topics

• Classification: Wirtschaft ; Optimization Techniques; Programming Models; Dynamic Analysis
• Subject: Lot-sizing ; Integration of Production Planning and Transportation ; Dynamic Programming ; Polynomial Time Algorithms ; Losgröße ; Produktionsplanung ; Lieferantenmanagement ; Logistik ; Dynamische Optimierung ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): van Hoesel, Stan ; Romeijn, H. Edwin ; Morales, Dolores Romero ; Wagelmans, Albert P.M.
• Event: Veröffentlichung
• (who): Tinbergen Institute
• (where): Amsterdam and Rotterdam
• (when): 2002

Further information

• Handle: http://hdl.handle.net/10419/85832
• Last update: 10.03.2025, 11:42 AM CET