Advanced planning and scheduling technology

This article presents research on the core technology in advanced planning and scheduling (APS) systems that are currently the state-of-art in supply chain planning and optimisation. Further research is needed to enable the opportunities given, especially the area of combined planning and scheduling...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Production planning & control Jg. 22; H. 8; S. 800 - 808
Hauptverfasser: Steger-Jensen, Kenn, Hvolby, Hans-Henrik, Nielsen, Peter, Nielsen, Izabela
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Taylor & Francis Group 01.12.2011
Taylor & Francis LLC
Schlagworte:
APS
Capital budgeting
Feasibility
Information systems
Integer programming
Linear programming
Logic programming
Mixed integer
optimisation
Optimization
Optimization techniques
Production planning
production planning and control
Programming
Resource allocation
Scheduling
Studies
Supply chain management
ISSN:0953-7287, 1366-5871
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This article presents research on the core technology in advanced planning and scheduling (APS) systems that are currently the state-of-art in supply chain planning and optimisation. Further research is needed to enable the opportunities given, especially the area of combined planning and scheduling. Mixed integer linear programming (MILP) methods have been successfully applied to solve diverse problems, such as planning and capital budgeting. Constraint programming (CP) methods have proved to be successful in solving highly constrained discrete optimisation and feasibility problems for scheduling and resource allocation and have been combined with MILP and titled Mixed linear logic programming (MLLP). In this article an integrated approach is presented that uses the complementary strengths of MILP and CP for solving problems that are otherwise intractable using either of these two methods alone. The presented optimisation approach can effectively handle the combined planning and scheduling problem within an APS system as part of the core optimisation engine.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0953-7287
1366-5871
DOI:10.1080/09537287.2010.543563