Dynamic scheduling model for the construction industry

Abstract

Purpose Basic project control through traditional methods is not sufficient to manage the majority of real-time events in most construction projects. The purpose of this paper is to propose a Dynamic Scheduling (DS) model that utilizes multi-objective optimization of cost, time, resources and cash flow, throughout project construction. Design/methodology/approach Upon reviewing the topic of DS, a worldwide internet survey with 364 respondents was conducted to define end-user requirements. The model was formulated and solution algorithms discussed. Verification was reported using predefined problem sets and a real-life case. Validation was performed via feedback from industry experts. Findings The need for multi-objective dynamic software optimization of construction schedules and the ability to choose among a set of optimal alternatives were highlighted. Model verification through well-known test cases and a real-life project case study showed that the model successfully achieved the required dynamic functionality whether under the small solved example or under the complex case study. The model was validated for practicality, optimization of various DS schedule quality gates, ease of use and software integration with contemporary project management practices. Practical implications Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste. Social implications Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste. Originality/value The paper illustrates the importance of DS in construction, identifies the user needs and overviews the development, verification and validation of a model that supports the generation of high-quality schedules beneficial to large-scale projects.