New competitive results for the stochastic resource-constrained project scheduling problem: exploring the benefits of pre-processing

Authors:
Behzad Ashtiani;Roel Leus;Mir-Bahador Aryanezhad
Affiliations:
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran;Department of Decision Sciences and Information Management, Katholieke Universiteit Leuven, Leuven, Belgium;Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Venue:
Journal of Scheduling
Year:
2011

Citing 13
Cited 0

Priority rules for job shops with weighted tardiness costs

Management Science
Scheduling of project networks by job assignment

Management Science
The role of the nonanticipativity constraint in commercial software for stochastic project scheduling

CIE '96 Proceedings of the 19th international conference on Computers and industrial engineering
New benchmark results for the resource-constrained project scheduling problem

Management Science
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Scheduling under uncertainty: Optimizing against a randomizing adversary

APPROX '00 Proceedings of the Third International Workshop on Approximation Algorithms for Combinatorial Optimization
A Graph-Theoretic Decomposition of the Job Shop Scheduling Problem to Achieve Scheduling Robustness

Operations Research
Scheduling Resource-Constrained Projects Competitively at Modest Memory Requirements

Management Science
When it is worthwhile to work with the stochastic RCPSP?

Journal of Scheduling
Augmenting priority rule heuristics with justification and rollout to solve the resource-constrained project scheduling problem

Computers and Operations Research
A two-stage-priority-rule-based algorithm for robust resource-constrained project scheduling

Computers and Industrial Engineering
Scheduling: Theory, Algorithms, and Systems

Scheduling: Theory, Algorithms, and Systems
Principles of Sequencing and Scheduling

Principles of Sequencing and Scheduling

Quantified Score

Hi-index	0.00

Visualization

Abstract

We study the resource-constrained project scheduling problem with stochastic activity durations. We introduce a new class of scheduling policies for solving this problem, which make a number of a-priori sequencing decisions in a pre-processing phase while the remaining decisions are made dynamically during project execution. The pre-processing decisions entail the addition of extra precedence constraints to the scheduling instance, hereby resolving some potential resource conflicts. We obtain new competitive results for expected-makespan minimization on representative datasets, which are significantly better than those obtained by the existing algorithms when the variability in the activity durations is medium to high.