Manuel Parente

An evolutionary multi-objective optimization system for earthworks

A novel system for dynamic optimization of earthworks is proposed.The system is based on an evolutionary multi-objective (cost-duration) approach.Results from several experiments using real-world data are presented.Results show the system is very competitive when compared to conventional design. Earthworks involve the leveling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

Combining Data Mining and Evolutionary Computation for Multi-criteria Optimization of Earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Small strain stiffness of sand under different isotropic and anisotropic stress paths measured by seismic wave-based testing techniques

Financial support provided by FCT (Portuguese Foundation for Science and Technology) in the form of the research project WaveSoil (PTDC/ECM/122751/2010).

Use of DM techniques in earthworks management: a case study

In most transportation infrastructure projects, earthworks are generally associated with the highest percentage costs and durations. Because these tasks are reliant on heavy machinery and repetitive tasks, they are strongly susceptible to optimization. This paper presents a study based on the application of artificial neural networks (ANN) on data originated from an actual earthwork construction project. Results show a good adjustment to the data while emphasizing the importance of optimal equipment allocation throughout the construction site. Finally, the architecture of an intelligent earthwork optimization system is presented, combining both data mining (DM) and modern optimization technologies, among others, to support equipment distribution optimization in earthwork projects.

Coupled ICT and Dynamic Optimization Tools Toward an Integrated Earthwork Management System

The main challenges of earthwork management are to optimize, in terms of time, costs and sustainability, the integration of several different tasks involved in the process. These tasks have to deal mainly with the geomaterials management (influencing excavation and compaction equipment as well as its use as a construction material) and equipment productivity (excavation, transport and compaction), under real environment conditions. To solve this complex management problem, a theoretical integrated system has been developed and evaluated for a database available of a real construction site.

Compaction Management: Results of a Demonstration Project

Compaction management, also referred to as intelligent compaction (IC), is a real time automatic operation adjustment and continuous compaction control technology of soils or asphalt layers. It is essentially a technology for optimization and evaluation of the compaction process, being capable of adjusting the compaction energy applied to the material, increasing or decreasing compaction efficiency in the necessary areas according to an acceptance target value, thus attaining maximum stiffness, while preventing overcompaction and minimizing the total number of passes. This study seeks to assess in a case study the IC performance, in comparison with conventional compaction methods in terms of efficiency in compaction of a sandy soil. For this purpose, a specific experimental section was carried out in which the performance of an IC compactor was compared with a conventional heavier class compactor. Data was obtained and analysed by the IC continuous information, as well as by the application of several different conventional compaction control tests and methods. Results show that the IC technology presents a superior performance, as well as various advantages when compared to conventional compactors.