Resource-Constrained Project Scheduling Under Uncertainty: Models, Algorithms and Applications

Abstract

This research aims to develop new optimization models and algorithms for project scheduling under both resource constraints and uncertainties, a problem known as the stochastic resource-constrained project scheduling problem (SRCPSP) in the operations research (OR) and scheduling literature. In a typical SRCPSP, a decision-maker attempts to obtain a feasible schedule of project tasks such that: (i) their temporal/precedence relationships are satisfied; (ii) the available resource capacity is not exceeded in each time period; and (iii) the expected project makespan is minimized. Using the developed modeling and solution methodologies, it is our goal to enhance the quality of decision support for scheduling complex large-scale projects in military, manufacturing, construction and professional service sectors.

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Document Details

Document Type
Technical Report
Publication Date
Nov 10, 2014
Accession Number
ADA617376

Entities

People

  • Haitao Li

Organizations

  • University of Missouri

Tags

Communities of Interest

  • Autonomy
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Business Administration
  • Dynamic Programming
  • Engineering
  • Manufacturing
  • Operations Research
  • Optimization
  • Probability
  • Probability Distributions
  • Production Planning
  • Students
  • Supply Chain
  • Systems Engineering
  • Technology Transfer
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Operations Research
  • Technical Research and Report Writing.