Automated trade‐off between time and cost in planning repetitive construction projects

An automated model is developed to support the optimization of the planning and scheduling of repetitive construction projects. The model provides the capability of optimizing two important objectives commonly sought in scheduling repetitive construction projects: minimizing project duration; and minimizing project cost. The model performs this multi‐objective optimization using a genetic algorithm approach. The output of the model is a set of optimal solutions that represent the trade‐off between time and cost in planning repetitive construction projects. Furthermore, the model can be utilized to find a single scheduling solution that provides the minimum overall project cost by simply adding project indirect cost to the obtained project direct cost for each of the obtained scheduling solutions on the Pareto optimal curve. Other important time‐related costs are also considered in the model including: early completion incentives, late completion penalties and lane rental costs. Providing the planners of repetitive construction projects with an automated set of optimal time–cost trade‐off solutions should contribute to cost‐effective and speedy delivery of this type of construction project. An application example is analysed to illustrate the use of the model and demonstrate its capabilities in generating optimal trade‐off solutions between minimizing the project time and cost for repetitive construction projects.     

Optimal Lighting Arrangements for Nighttime Highway Construction Projects

This paper presents a decision support system for optimizing temporary lighting arrangements in nighttime highway construction projects. The system is developed as a multiobjective genetic algorithm that is capable of: (1) maximizing average illuminance on construction sites; (2) maximizing lighting uniformity in the work zone; (3) minimizing glare to workers and road users; and (4) minimizing lighting costs. The system is designed to support decision makers in their search for practical lighting arrangements that provide various tradeoffs among these four conflicting objectives. Five decision variables are optimized in the present system, namely: number of lighting equipment, equipment positioning, mounting height, aiming angle, and rotation angle. The system is also designed to consider and satisfy all practical constraints that can be encountered in this lighting design problem. An application example is analyzed to illustrate the use of the system and demonstrate its capabilities in generating near optimal and practical lighting arrangements for nighttime highway construction projects.     

CONLIGHT: Lighting Design Model for Nighttime Highway Construction

The utilization of nighttime work in highway construction and rehabilitation projects has been increasing in recent years throughout the United States. In this type of projects, construction planners are required to develop and submit a lighting plan that provides: (1) adequate illuminance levels for all planned nighttime construction tasks; (2) reasonable uniformity of light distribution in the work area, and (3) acceptable glare levels to both road users and construction workers. In order to support construction planners in this vital and challenging task, this paper presents a lighting design model, named CONLIGHT, which is capable of considering the specific requirements of nighttime highway construction operations. The model is developed to enable construction planners to evaluate the performance of various lighting plans and select a practical design that complies with all lighting requirements for the nighttime work being planned. An application example is analyzed to illustrate the use of the model and demonstrate its accuracy and capabilities in generating practical lighting plans for nighttime construction and rehabilitation projects.     

Lighting Requirements for Nighttime Highway Construction

This paper presents the development of a practical framework for identifying the lighting requirements for nighttime highway construction activities. The framework is named Construction Visual Requirements, “CONVISUAL,” and is designed to consider and quantify the varying lighting needs for different visual and construction tasks. The framework is developed using an original and interdisciplinary approach that integrates concepts and models from construction engineering and vision science to ensure the provision of adequate lighting conditions on site that enable workers to properly see and perform their tasks safely and with satisfactory quality. CONVISUAL determines the required illuminance level for each construction activity based on its required visual tasks and the visual capacity of construction workers. A prototype of CONVISUAL framework is implemented to illustrate its unique capabilities of (1) providing a deeper understanding of the visual requirements of nighttime construction activities; (2) specifying the required illuminance levels in a scientific and systematic approach; and (3) delivering a rational justification for the specified illuminance levels.     

Optimal Planning and Scheduling for Repetitive Construction Projects

This paper presents a multiobjective optimization model for the planning and scheduling of repetitive construction projects. The model enables construction planners to generate and evaluate optimal construction plans that minimize project duration and maximize crew work continuity, simultaneously. The computations in the present model are organized in three major modules: scheduling, optimization, and ranking modules. First, the scheduling module uses a resource-driven scheduling algorithm to develop practical schedules for repetitive construction projects. Second, the optimization module utilizes multiobjective genetic algorithms to search for and identify feasible construction plans that establish optimal tradeoffs between project duration and crew work continuity. Third, the ranking module uses multiattribute utility theory to rank the generated plans in order to facilitate the selection and execution of the best overall plan for the project being considered. An application example is analyzed to illustrate the use of the model demonstrate its new capabilities in optimizing the planning and scheduling of repetitive construction projects.     

Utilizing data envelopment analysis to benchmark safety performance of construction contractors

The purpose of this paper is to utilize data envelopment analysis (DEA) to benchmark safety performance of construction contractors. DEA has been recognized as a robust tool that is used for evaluating the performance of business organizations. The proposed approach is deployed based on empirical data collected from 45 construction contractors. On a scale of 0–1.0, DEA analysis assesses the relative efficiency of every contractor relative to the rest of the contractors in terms of safety performance. For inefficient contractors, DEA analysis provides quantitative guidance on how to become efficient.