Resource allocation and planning for program management

• Published in: 2005 Winter Simulation pp. 2127 - 2135
• Main Authors: Vaziri, Kabeh, Nozick, Linda K., Turnquist, Mark A.
• Format: Conference Proceeding
• Language: English
• Published: Winter Simulation Conference 04.12.2005
• Series: ACM Conferences
• Subjects: Computing methodologies; Computing methodologies > Artificial intelligence; Computing methodologies > Artificial intelligence > Search methodologies; Computing methodologies > Artificial intelligence > Search methodologies > Heuristic function construction; Theory of computation; Theory of computation > Design and analysis of algorithms; Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis; Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis > Scheduling algorithms; Theory of computation > Design and analysis of algorithms > Mathematical optimization; Theory of computation > Design and analysis of algorithms > Online algorithms; Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms; Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms > Scheduling algorithms; Theory of computation > Theory and algorithms for application domains; Theory of computation > Theory and algorithms for application domains > Machine learning theory; Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning; Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning > Sequential decision making
• ISBN: 0780395190; 9780780395190
• DOI: 10.5555/1162708.1163079

Much of the project scheduling literature treats task durations as deterministic. In reality, however, task durations are subject to considerable uncertainty and that uncertainty can be influenced by the resources assigned. The purpose of this paper is to provide the means for program managers (who may have responsibility for multiple projects) to optimally allocate resources from common resource pools to individual tasks on several competing projects. Instead of the traditional use of schedules, we develop control policies in the form of planned resource allocation to tasks that capture the uncertainty associated with task durations and the impact of resource allocation on those durations. We develop a solution procedure for the model and illustrate the ideas in an example.