Optimized scheduling and buffering of repetitive construction projects under uncertainty

Abstract

Purpose Construction projects are complex projects taking place in dynamic environments, which necessitates accounting for different uncertainties during the planning stage. There is a significant lack of management tools for repetitive projects accounting for uncertainties in the construction environment. The purpose of this paper is to present an algorithm for the optimized scheduling of repetitive construction projects under uncertainty. Design/methodology/approach Fuzzy set theory is utilized to model uncertainties associated with various input parameters. The developed algorithm has two main components: optimization component and buffering component. The optimization component presents a dynamic programming approach that processes fuzzy numbers. The buffering component converts the optimized fuzzy schedule into a deterministic schedule and inserts time buffers to protect the schedule against anticipated delays. Agreement Index (AI) is used to capture the user’s desired level of confidence in the produced schedule while sizing buffers. The algorithm is capable of optimizing for cost or time objectives. An example project drawn from literature is analysed to demonstrate the capabilities of the developed algorithm and to allow comparison of results to those previously generated. Findings Testing the algorithm revealed several findings. Fuzzy numbers can be utilized to capture uncertainty in various inputs without the need for historical data. The modified algorithm is capable of optimizing schedules, for different objectives, under uncertainty. Finally AI can be used to capture users’ desired confidence in the final schedule. Originality/value Project planners can utilize this algorithm to optimize repetitive projects schedules, while modelling uncertainty in different input parameters, without the need for relevant historical data.

Preferences of Construction Managers Regarding the Quality and Optimization Criteria of Project Schedules

“…These specific, complex conditions for the realization of construction projects significantly distinguish them from the realization of projects from other branches of the economy. As a result, the existing project management support tools are not suited to the problems in the construction industry [9][10][11][12][13][14]. For this reason, scientists are developing ever new tools to support construction managers [15,16].…”

Robustness-based multi-objective optimization for repetitive projects under work continuity uncertainty

“…Another commonly used method to handle uncertainty is critical chain project management (CCPM), which develops a schedule using buffers to avoid delay. Bakry et al (2016) produced a deterministic schedule and a buffer component using a proposed fuzzy algorithm that inserts buffers with consideration given to unit duration and costs uncertainties. Salama et al (2017) presented a scheduling model that deals with uncertainty in activity duration based on an integration of linear scheduling method (LSM) and CCPM.…”

Alternative Scheduling and Planning Processes for Hybrid Offsite Construction

“…Dressler [18] considered uncertainty for a project by assigning probability distributions to each project segment however this approach requires complex linear programming methods to develop a schedule. Other researchers developed simulation-based methods [19], [20], and [21] and fuzzy set-based methods [22] and [23] to account for uncertainty associated with linear scheduling. However, these methods either depend on data availability, third party software, or tailored for a specific type of repetitive projects.…”