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Development of quantitative methods for project scheduling and workface planning under time-dependent resource constraints

  • Author / Creator
    Siu, Ming Fung
  • Analytical decision support for project scheduling and workface planning under time-dependent resource constraints is limited in industrial-construction. Previous project scheduling research endeavors in the construction engineering and management domain focused on formulating resource-constrained project schedules by use of simulation and optimization techniques in order to shorten the total project duration based on the classic critical path method (CPM), subject to fixed resource supply over project period. Nonetheless, the following critical factors have not been adequately considered and thoroughly treated in devising quantitative solutions, namely: (i) the thresholds of resource supply limits considered being sufficient to complete the project in the shortest possible duration, (ii) the varied resource provisions over different time periods during the project duration, and (iii) the sufficiency of the control budget for executing the formulated project schedule, and the efficiency of the deployed resources utilized when executing the formulated project schedule. Tackling the defined problems provides the motivation to deliver the present research. First, the resource supply-demand matching problem (RSDMP) approach is mathematically developed for scheduling construction projects with resource constraints. The result is an optimum resource-constrained schedule providing the shortest project duration with the leanest resource supply. The optimum resource requirement is identified between the lower and upper boundaries of resource supply limit. The optimum resource workflows of individual craft persons are presented. Next, a modified RSDMP approach is mathematically formalized aiming to generate the optimum resource-constrained project schedule under time-dependent resource constraints. The resulting optimum schedule shortens total project duration while streamlining resource supply for each specified project time period. The computational efficiency of applying the modified RSDMP approach to the construction project with practical size and complexity is examined. Then, a quantitative assessment approach is developed for mathematically characterizing budget sufficiency and resource utilization for a resource-constrained project schedule in an objective fashion. The method is applied for evaluating and visualizing budget sufficiency and resource utilization to assess multiple alternative resource-constrained project schedules as derived from any resource-based scheduling approaches, such as the practical scheduling approach (Primavera P6) and schedule optimization techniques (RSDMP approaches). In close collaboration with a major contractor of industrial-construction in Alberta Canada, the practical application needs have been identified on plant shutdown and maintenance projects to justify the problem statement for this research and motivate its solution formulations. As such, apart from the example case studies adapted from textbooks used to illustrate the developed quantitative scheduling techniques, a plant shutdown and maintenance project serves a real-world case to demonstrate the applications of the developed approaches in practical settings. The academic contributions of this research work are demonstrated by the development of quantitative scheduling methods developed for planning industrial-construction project. The resource supply-demand matching problem (RSDMP) is generalized; while formalizing the RSDMP approach which consists of a mathematical model, a two-stage optimization approach, and an innovative use of a refined resource-activity interaction table. The RSDMP approach is then modified in coping with time-dependent resource constraints. The analytical metrics of budget sufficiency and resource utilization are defined from project scheduling perspectives, including budgeted units, deployed units, scheduled units, budget sufficiency index, budget sufficiency variance, resource utilization index, and resource utilization variance. The industrial contributions of this research work are demonstrated by the implementation of the developed methods to improve the existing practice of planning plant shutdown and maintenance projects. In practice, the resources are budgeted and allocated based upon the rough estimate of resource supply for matching resource demand throughout the project duration. The assessment of budget sufficiency and resource utilization are commonly made based on experience. In contrast, the optimum RSDMP schedule is practically feasible and workface executable. The modified RSDMP optimum plan avoids undersupply and oversupply of resources for particular time periods. The budget sufficiency index/variance and resource utilization index/variance provide analytical bases to justify increasing the project budget or performing schedule optimization to effectively cope with contingencies (including unexpected work during project planning stage). In reality, this is inevitable during project execution. In essence, the developed planning methodologies not only make academic contribution by advancing the state-of-the-art in construction engineering and management, but also remain practically relevant to the critical industrial-construction planning practice, enabling project managers, project schedulers, and field superintendents to make informed, sound decisions in terms of project scheduling, resource allocation, and project budgeting.

  • Subjects / Keywords
  • Graduation date
    Spring 2016
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R36688Q4G
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.