Automation in construction scheduling: a review of the literature

Abstract

Automating the development of construction schedules has been an interesting topic for researchers around the world for almost three decades. Researchers have approached solving scheduling problems with different tools and techniques. Whenever a new artificial intelligence or optimization tool has been introduced, researchers in the construction field have tried to use it to find the answer to one of their key problems-the "better" construction schedule. Each researcher defines this "better" slightly different. This article reviews the research on automation in construction scheduling from 1985 to 2014. It also covers the topic using different approaches, including case-based reasoning, knowledge-based approaches, model-based approaches, genetic algorithms, expert systems, neural networks, and other methods. The synthesis of the results highlights the share of the aforementioned methods in tackling the scheduling challenge, with genetic algorithms shown to be the most dominant approach. Although the synthesis reveals the high applicability of genetic algorithms to the different aspects of managing a project, including schedule, cost, and quality, it exposed a more limited project management application for the other methods.

A simulation-based approach for optimal construction planning and scheduling

“…Automation in scheduling has been studied mainly in the last three decades and several approaches were experimented [1]. Cased-based reasoning (CB) is able to exploit the specific knowledge of formerly practiced situations and compares present problems with an earlier situation, which is then used to solve and explain the new problem [4].…”

“…The often scarce communication and the absence of automation requires the adoption of standard methods, such as face-to-face meetings and paperwork. This approach has been identified as an inhibitor to increasing productivity and a frequent source of miscommunication and rework [1]. To solve the problem of insufficient information and sub-optimal planning, researchers turned towards automating the process of generating schedules.…”

“…In this paper, we will mainly focus on computational tools and on information handling. As far as computation is concerned, in the past decades a number of solutions were suggested, ranging from case-based and knowledge-based reasoning to model-based simulation, until the latest approaches inspired from artificial intelligence [1]. More recently, thanks to the advent of powerful computational tools, the potential of agent-based simulation was highlighted, and first applications in the field of optimal planning were produced.…”

Objective-driven and Pareto Front analysis: Optimizing time, cost, and job-site movements

“…Several successful attempts have been conducted to show this relationship. Different optimization tools have been applied to find the time-cost relationship of projects [10]. In most cases, optimization tools that can produce numerous outputs while optimizing the solutions (e.g., genetic algorithm) are selected for this type of research.…”

Crew Allocation System for the Masonry Industry

“…Koo et al (2016) developed a multi-objective optimization model for vertical transportation of lift cars for workers in a skyscrapper construction. A review of the aspects and modelling approaches in personnel allocation in construction can be found in Brucker et al (2011), Zhou et al (2013) and Faghihi et al (2015).…”