NDLI: Knowledge integration using problem spaces: A study in resource-constrained project scheduling

Content Provider	Springer Nature Link
Author	Padman, Rema Zhu, Dan
Copyright Year	2006
Abstract	The need to develop schedules for projects with resource constraints and cash flows arises in organizational settings ranging from construction planning to research and development. Given the intractable nature of the problem, a variety of knowledge sources relevant to the project scheduling task have been identified in the Operations Management literature. These include a large number of heuristic procedures that can be used to generate feasible project schedules as well as recent neural network-based approaches that can select appropriate heuristic procedures to apply to a specific instance of the project scheduling problem. While integrated application of these knowledge sources is required to effectively support scheduling, previous work has focussed on developing and implementing them in isolation. The problem space computational model presented in this paper addresses this shortcoming by integrating these various knowledge sources, thus enabling the development of decision support systems for resource constrained project scheduling. More generally, the modeling approach used in this paper can be applied to create systems to assist knowledge intensive tasks that arise in many organizational settings.
Starting Page	133
Ending Page	152
Page Count	20
File Format	PDF
ISSN	10946136
Journal	Journal of Scheduling
Volume Number	9
Issue Number	2
e-ISSN	10991425
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2006-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Knowledge integration Constrained project scheduling Neural networks Heuristics Artificial Intelligence (incl. Robotics) Optimization Calculus of Variations and Optimal Control Operations Research/Decision Theory Production/Logistics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Management Science and Operations Research Engineering Software

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