Computing the Envelope for Stepwise-Constant Resource Allocations

Authors:
Nicola Muscettola
Affiliations:
-
Venue:
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Year:
2002

Citing 10
Cited 11

A new approach to the maximum-flow problem

Journal of the ACM (JACM)
Introduction to algorithms

Introduction to algorithms
Temporal constraint networks

Artificial Intelligence - Special issue on knowledge representation
Look-ahead techniques for micro-opportunistic job shop scheduling

Look-ahead techniques for micro-opportunistic job shop scheduling
Intelligent scheduling

Intelligent scheduling
On the utility of bottleneck reasoning for scheduling

AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Algorithms for propagating resource constraints in AI planning and scheduling: existing approaches and new results

Artificial Intelligence
A Time and Resource Problem for Planning Architectures

ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Dynamic control of plans with temporal uncertainty

IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Beyond contention: extending texture-based scheduling heuristics

AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence

Continuous refinement of agent resource estimates

AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Scheduling with uncertainty: A proactive approach using Partial Order Schedules: Thesis

AI Communications
From precedence constraint posting to partial order schedules: A CSP approach to Robust Scheduling

AI Communications - Constraint Programming for Planning and Scheduling
A Continuous Multi-resources cumulative Constraint with Positive-Negative Resource Consumption-Production

CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Solve-and-robustify

Journal of Scheduling
A theoretic and practical framework for scheduling in a stochastic environment

Journal of Scheduling
An effective algorithm for project scheduling with arbitrary temporal constraints

AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Tractable classes of metric temporal problems with domain rules

AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Resource temporal networks: definition and complexity

IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A precedence constraint posting approach for the RCPSP with time lags and variable durations

CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling

Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Computing tight resource-level bounds is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with nodes equal to the events and edges equal to the necessary predecessor links between events. A staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. Each stage has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible and promising for use in the inner loop of flexible-time scheduling algorithms.