Level: Advanced
TCM Section(s)
11.3. Information Management
7.2. Schedule Planning and Development
Venue: 2024 AACE International Conference & Expo
Abstract: This paper investigates the application of optimization techniques to develop schedule scenarios with different relationships between activities, with an emphasis on reducing environmental emissions in terms of global warming potential (GWP) CO2-equivalent. The research team has investigated the potential improvement of its previously developed in-house method of integrating environmental sustainability metrics with critical path method (CPM) schedules, by using metaheuristics and optimization techniques. This previously developed novel method estimates 100-year global warming potential (GWP) CO2-equivalent emissions as a function of the CPM schedule at an activity level. The intent of this paper is to explore further automation and optimization of certain aspects of this method of estimating sustainability metrics.
Moreover, the application of optimization techniques to develop schedule scenarios with different relationships between activities with an emphasis on reducing environmental emissions in terms of global warming potential (GWP) CO2-equivalent is investigated. Prior researchers have applied metaheuristics like the genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), ant colony optimization (ACO), etc., to develop schedules with minimum overall duration under the constraints of limited resources. With a focus on GA, the authors investigate the real-world applications of metaheuristics to optimize critical path method (CPM)- based project schedules. This investigation also provided the opportunity to explore further automation and optimization of certain aspects of this methodology for estimating sustainability metrics.
This paper builds on this research group’s previous article presented and published in AACE International Transactions 2023 (PS-4044)..
TCM Section(s)
11.3. Information Management
7.2. Schedule Planning and Development
Venue: 2024 AACE International Conference & Expo
Abstract: This paper investigates the application of optimization techniques to develop schedule scenarios with different relationships between activities, with an emphasis on reducing environmental emissions in terms of global warming potential (GWP) CO2-equivalent. The research team has investigated the potential improvement of its previously developed in-house method of integrating environmental sustainability metrics with critical path method (CPM) schedules, by using metaheuristics and optimization techniques. This previously developed novel method estimates 100-year global warming potential (GWP) CO2-equivalent emissions as a function of the CPM schedule at an activity level. The intent of this paper is to explore further automation and optimization of certain aspects of this method of estimating sustainability metrics.
Moreover, the application of optimization techniques to develop schedule scenarios with different relationships between activities with an emphasis on reducing environmental emissions in terms of global warming potential (GWP) CO2-equivalent is investigated. Prior researchers have applied metaheuristics like the genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), ant colony optimization (ACO), etc., to develop schedules with minimum overall duration under the constraints of limited resources. With a focus on GA, the authors investigate the real-world applications of metaheuristics to optimize critical path method (CPM)- based project schedules. This investigation also provided the opportunity to explore further automation and optimization of certain aspects of this methodology for estimating sustainability metrics.
This paper builds on this research group’s previous article presented and published in AACE International Transactions 2023 (PS-4044)..