Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning

The use of modular construction has gained wide acceptance in the industry. For a specific construction facility layout problem such as site precast standardized modular units, it requires the establishment of an on-site precast yard. Arranging the precast facilities within a construction site presents real challenge to site management. This complex task is further augmented with the involvement of several resources and different transport costs. A genetic algorithm (GA) model was developed for the search of a near-optimal layout solution. Another approach using mixed-integer programming (MIP) has been developed to generate optimal facility layout. These two approaches are applied to solve with an example in this paper to demonstrate that the solution quality of MIP outperforms that of GA. Further, another scenario with additional location constraints can also be solved readily by MIP, which, however, if modeled by GA, the solution process would be complicated. The study has highlighted that MIP can perform better than GA in site facility layout problems in which the site facilities and locations can be represented by a set of integer variables.     

Dynamic Site Layout Planning Using Approximate Dynamic Programming

Dynamic site layout planning requires identifying and updating the positions of all temporary construction facilities such as offices, storage areas, and workshops over the entire project duration. Existing models do not guarantee global optimal solutions because they focus on optimizing the planning and layout of successive construction stages in a chronological order, without considering the future implications of layout decisions made in early stages. This paper presents the development of an approximate dynamic programming model that is capable of searching for and identifying global optimal dynamic site layout plans. The model applies the concepts of approximate dynamic programming to estimate the future effects of layout decisions in early stages on future decisions in later stages. The model is developed in three main phases: (1) formulating the decision variables, geometric constraints, and objective function of the dynamic site layout planning problem; (2) modeling the problem using approximate dynamic programming; and (3) implementing and evaluating the performance of the model. An evaluation example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating global optimal solution for dynamic site layout planning of construction projects.     

Trade-off between Safety and Cost in Planning Construction Site Layouts

Planning construction site layouts involves identifying the positions of temporary facilities on site, and accordingly it has a significant impact on the safety and efficiency of construction operations. Although available models are capable of minimizing the travel cost of resources on site, they do not consider safety as an important and separate objective in the optimization of site layouts. This paper presents the development of an expanded site layout planning model that is capable of maximizing construction safety and minimizing the travel cost of resources on site, simultaneously. The model incorporates newly developed concepts and performance criteria that enable the quantification of construction safety and travel cost of resources on site. The present model is developed in three main phases: (1) formulating decision variables and optimization objectives in this site layout planning problem; (2) identifying and satisfying all practical constraints in this optimization problem; and (3) implementing the model as a multiobjective genetic algorithm. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing construction site layouts and generating optimal trade-offs between safety and travel cost of resources on site.     

Conjoining MMAS to GA to Solve Construction Site Layout Planning Problem

An optimal construction site layout planning (CSLP) is vital for project management. It can reduce the transportation flows and thus the costs of a project. Genetic algorithm (GA) is the most used algorithm to solve site layout problems, but randomly generated initial population in GA will decrease solution quality. Max-min ant system (MMAS) can offer a better initial population than the randomly generated initial population at the beginning of GA. In this study, a modified GA (MMAS-GA) formed by conjoining MMAS to the step of initialization of GA is proposed to solve CSLP problems. In order to reveal the computational capability of MMAS-GA to solve CSLP problems, the results of MMAS-GA and traditional GA are compared by solving an equal-area CSLP problem. The results showed that the proposed MMAS-GA algorithm provided a better optimal solution under the objective function of minimizing the transportation flows between the site facilities. The proposed MMAS-GA algorithm could assist project managers and planners to design optimal construction site layout, and thus to reduce construction costs.     

Optimal Construction Site Layout Considering Safety and Environmental Aspects

A good site layout is vital to ensure the safety of the working environment and effective and efficient operations. Site layout planning has significant impacts on productivity, costs, and duration of construction. Construction site layout planning involves identifying, sizing, and positioning temporary and permanent facilities within the boundary of the construction site. Site layout planning can be viewed as a complex optimization problem. Although construction site layout planning is a critical process, systematical analysis of this problem is always difficult because of the existence of a vast number of trades and interrelated planning constraints. The problem has been solved using two distinct approaches: Optimization techniques and heuristics methods. Mathematical optimization procedures have been developed to produce optimal solutions, but they are only applicable for small-size problems. Artificial intelligent techniques have been used practically to handle real-life problems. On the other hand, heuristic methods have been used to produce good but not optimal solutions for large problems. In this paper, an optimization model has been developed for solving the site layout planning problem considering safety and environmental issues and actual distance between facilities. Genetic algorithms are used as an optimization bed for the developed model. In order to validate the performance of the developed model, a real-life construction project was tested. The obtained results proved that satisfactory solutions were obtained.     

Error checking and graphical representation of multiple-complete-digest (MCD) restriction-fragment maps

Genetic and physical maps display the relative positions of objects or markers occurring within a target DNA molecule. In constructing maps, the primary objective is to determine the ordering of these objects. A further objective is to assign a coordinate to each object, indicating its distance from a reference end of the target molecule. This paper describes a computational method and a body of software for assigning coordinates to map objects, given a solution or partial solution to the ordering problem. We describe our method in the context of multiple-complete-digest (MCD) mapping, but it should be applicable to a variety of other mapping problems. Because of errors in the data or insufficient clone coverage to uniquely identify the true ordering of the map objects, a partial ordering is typically the best one can hope for. Once a partial ordering has been established, one often seeks to overlay a metric along the map to assess the distances between the map objects. This problem often proves intractable because of data errors such as erroneous local length measurements (e.g., large clone lengths on low-resolution physical maps). We present a solution to the coordinate assignment problem for MCD restriction-fragment mapping, in which a coordinated set of single-enzyme restriction maps are simultaneously constructed. We show that the coordinate assignment problem can be expressed as the solution of a system of linear constraints. If the linear system is free of inconsistencies, it can be solved using the standard Bellman-Ford algorithm. In the more typical case where the system is inconsistent, our program perturbs it to find a new consistent system of linear constraints, close to those of the given inconsistent system, using a modified Bellman-Ford algorithm. Examples are provided of simple map inconsistencies and the methods by which our program detects candidate data errors and directs the user to potential suspect regions of the map.     

Particle Swarm Optimization for Construction Site Unequal-Area Layout

Layout of temporary facilities on a construction site is essential to enhancing productivity and safety, and is a complex issue due to the unique nature of construction. This paper proposes a particle swarm optimization (PSO)-based methodology to solve the construction site unequal-area facility layout problem. A priority-based particle representation of the candidate solutions to the layout problem is proposed. The particle-represented solution in terms of priorities should be transformed to the specific layout plan with consideration of nonoverlap and geometric constraints. In addition, a modified solution space boundary handling approach is proposed for controlling particle updating with regard to the priority value range. Computational experiments are carried out to justify the efficiency of the proposed method and investigate its underlying performances. This study aims at providing an alternative and effective means for solving the construction site unequal-area layout problem by utilizing the PSO algorithm.     

Distributed Augmented Reality for Visualizing Collaborative Construction Tasks

Augmented reality is a visualization method in which virtual objects are aligned with the real world and the viewer can interact with the virtual objects in real time. In this paper, a new methodology called distributed augmented reality for visualizing collaborative construction tasks (DARCC) is proposed. Using this methodology, virtual models of construction equipment can be operated and viewed by several operators to interactively simulate construction activities on the construction site in augmented reality mode. The paper investigates the design issues of DARCC including tracking and registration, object modeling, engineering constraints, and interaction and communication methods. The DARCC methodology is implemented in a prototype system and tested in a case study about a bridge deck rehabilitation project.     

Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities

This paper presents an investigation of the applicability of a genetic approach for solving the construction site layout problem. This problem involves coordinating the use of limited site space to accommodate temporary facilities so that transportation cost of materials is minimized. The layout problem considered in this paper is characterized by affinity weights used to model transportation costs between facilities and by geometric constraints that limit their relative positions on site. The proposed genetic algorithm generates an initial population of layouts through a sequence of mutation operations and evolves the layouts of this population through a sequence of genetic operations aiming at finding an optimal layout. The paper concludes with examples illustrating the strength and limitations of the proposed algorithm in the cases of (1) loosely versus tightly constrained layouts with equal levels of interaction between facilities; (2) loosely versus tightly packed layouts with variable levels of interactions between facilities; and (3) loosely versus tightly constrained layouts. In most problems considered where the total-objects-to-site-area ratio did not exceed 60%, the algorithm returned close to optimal solutions in a reasonable time.     

Identification and Resolution of Work Space Conflicts in Building Construction

Numerous workers, equipment, material, temporary facilities, as well as permanent structures share the limited space during construction. Since space constraints may affect productivity and the critical path, it is essential to organize the available space efficiently and minimize space conflicts. This study considers space availability due to time and scheduling, productivity loss due to space constraints and path interference, as well as the possibility of alternative space to resolve these conflicts and optimize space usage. Herein, computer-aided design is integrated with scheduling software for the dynamic identification of space conflicts on the jobsite. Follow-up supplemental decision criteria are then provided for conflict analysis and resolution. A prototype decision support system that combines the criteria was developed to solve this significant and complex problem more efficiently and precisely. A case study demonstrates the use and development of this system, which is very helpful to engineers and project managers.     

Measuring Safety Climate of a Construction Company

Safety climate can benefit contractors, specialty contractors, and owners of industries by providing them with the knowledge of attitudes and perceptions that can help to consistently achieve better safety performance. The objective of this research was to determine safety climate that would enhance safety culture and positively impact perceived safety performance on construction projects. A safety climate questionnaire survey was conducted on the construction sites of a leading construction company and its subcontractors in Hong Kong. Approximately, 1,500 hard copy questionnaires were distributed and the response rate was excellent, resulting in 1,120 valid questionnaires being collected from 22 construction projects. By means of factor analysis, two underlying safety climate factors were extracted, accounting for 43.9% of the total variance. Multiple regression analysis confirmed that these climate factors, “management commitment and employee involvement” and “inappropriate safety procedure and work practices” were significant predictors of workers’ perceptions of safety performance. The findings indicated that the relationship between perceived safety performance and “inappropriate safety procedure and work practices” was inversely correlated. The results suggest that safety climate can be used as an effective measure of assessing and improving site safety for projects under construction. The findings of this study and the methodology might be useful for research at other construction sites in other regions and countries. This work provides useful information for project managers and safety practitioners who desire to improve safety climate and safety performance on construction sites.     

Leonardo's constraint: Two opaque objects cannot be seen in the same direction.

Given Leonardo's constraint that 2 opaque objects cannot be seen in the same direction, how are the regions of objects occluded to 1 eye included in perception? To answer this question, the authors presented 3-dimensional stimuli, similar to the ones that concerned Leonardo, and measured the visual directions of their monocular and binocular regions. When the distance between near and far objects was large, the nonfixated object was seen as double and blurry. Leonardo's constraint was met by seeing the near object as double and transparent or the distant object as double and superimposed. When the distance between near and far objects was small, the constraint was met by a perceptual displacement and compression of parts of the nonfixated object. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Finance-Based Scheduling of Construction Projects Using Integer Programming

Construction scheduling is the process of devising schemes for sequencing activities. A realistic schedule fulfills the real concerns of users, thus minimizing the chances of schedule failure. The minimization of total project duration has been the concept underlying critical-path method/program evaluation and review technique (CPM/PERT) schedules. Subsequently, techniques including resource management and time-cost trade-off analysis were developed to customize CPM/PERT schedules in order to fulfill users’ concerns regarding project resources, cost, and time. However, financing construction activities throughout the course of the project is another crucial concern that must be properly treated otherwise, nonrealistic schedules are to be anticipated. Unless contractors manage to procure adequate cash to keep construction work running according to schedule, the pace of work will definitely be relaxed. Therefore, always keeping scheduled activities in balance with available cash is a potential contribution to producing realistic schedules. This paper introduces an integer-programming finance-based scheduling method to produce financially feasible schedules that balance the financing requirements of activities at any period with the cash available during that same period. The proposed method offers twofold benefits of minimizing total project duration and fulfilling finance availability constraints.     

Challenges in Line-of-Balance Scheduling

The line-of-balance (LOB) method of scheduling is well suited to projects that are composed of activities of a linear and repetitive nature. The objective of this study is to set down the basic principles that can be used in the development of a computerized LOB scheduling system that overcomes the problems associated with existing systems and creates solutions to problems encountered in the implementation of repetitive-unit construction. The challenges associated with LOB scheduling include developing an algorithm that handles project acceleration efficiently and accurately, recognizing time and space dependencies, calculating LOB quantities, dealing with resource and milestone constraints, incorporating the occasional nonlinear and discrete activities, defining a radically new concept of criticalness, including the effect of the learning curve, developing an optimal strategy to reduce project duration by increasing the rate of production of selected activities, performing cost optimization, and improving the visual presentation of LOB diagrams.     

Segmental Post‐Tensioned Dolphin at Tagrin Point

The nature and extent of resource constraints on projects in developing countries are described in the context of the construction of the dolphin at Tagrin Point in Sierra Leone, West Africa. The interplay between what is possible and what is feasible given the constrained resources is considered in terms of various design alternatives. A new type of ship breasting structure evolving from the construction constraints proves to be functional and promising. The segmental, post‐tensioned dolphin not only meets the structural and functional requirements but, in making use of appropriate modern technologies, resolved the constructional problems on this project and in so doing, opens up a new field in the design and construction of berthing facilities, with the possibility of changing many concepts and previous constraints.     

Time-Cost Optimization of Construction Projects with Generalized Activity Constraints

Time-cost analysis is an important element of project scheduling, especially for lengthy and costly construction projects, as it evaluates alternative schedules and establishes an optimum one considering any project completion deadline. Existing methods for time-cost analysis have not adequately considered typical activity and project characteristics, such as generalized precedence relationships between activities, external time constraints, activity planning constraints, and bonuses/penalties for early/delayed project completion that would provide a more realistic representation of actual construction projects. The present work aims to incorporate such characteristics in the analysis and has developed two solution methods, an exact and an approximate one. The exact method utilizes a linear/integer programming model to provide the optimal project time-cost curve and the minimum cost schedule considering all activity time-cost alternatives together. The approximate method performs a progressive project length reduction providing a near-optimal project time-cost curve but it is faster than the exact method as it examines only certain activities at each stage. In addition, it can be easily incorporated in project scheduling software. Evaluation results indicate that both methods can effectively simulate the structure of construction projects, and their application is expected to provide time and cost savings.     

Optimal Project Organizational Structure for Construction Management

This study relies on the trend model to investigate various modes of coordination among team members of construction projects. According to the project network developed based on the characteristics of a project, the trend model establishes an activity relationship matrix (ARM) to identify the activity relationships within the construction process. ARM is used to construct an organizational structure for project management and a communication resistance matrix that shows the efficiency of communication and coordination among the members of the project team. To evaluate various organizational structures and their coordination efficiencies, this study utilizes the analytical hierarchy process to quantify the strength of an organizational structure and identify the optimal structure for project management. Through quantitative modeling of communication efficiency among organizational team members, an objective function for calculating the total resistance index is used to determine the optimal organizational structure available to execute the project. This study demonstrates how the trend model may be applied in the future for evaluating the coordination efficiencies of various organizational structures.     

Baseline Determination in Construction Labor Productivity-Loss Claims

Various ways of quantifying damages have been applied to productivity loss claims in construction. All of the ways attempt to be as objective as possible based on the extent of information available in a particular case. The measured mile, a widely accepted method, is employed when an unimpacted baseline period of production can be identified. Although that approach is considered to be the most objective method available in such cases, the method is limited and does not directly account for variation in individual productivity values about a normal or natural level of productivity. A gap exists between the use of existing methods and the availability of an appropriate methodology that specifically addresses variation in productivity. The key lies in the way baseline productivity is measured, which is inherently statistical, yet no truly statistical methods are used to establish such a baseline. Using the measured mile as a backdrop, this article provides an objective, measurement-based approach that can be used to establish a productivity baseline applied to construction productivity loss claims, based on the application of statistical methods aided by a process control chart. The focus is on providing the basic principles and concepts underlying the approach presented.     

Computer-Aided Site Layout Planning

This paper presents an interactive computer-aided site layout model to support site planning in a computer-aided design (CAD) environment and expands upon a model presented earlier by the writers. The developed model performs its task at two levels: Site representation, and site space analysis and allocation. The site representation is carried out using an open architecture supported by object-based concepts. The model offers three tiers of objects: (1) site objects, (2) construction objects, and (3) constraint objects. This structure facilitates the creation of new objects and reuse of domain knowledge, which allows for the gradual expansion and enrichment of the model’s knowledge base. At the space analysis and allocation level, the model introduces a geometric reasoning approach to analyze site space for finding an optimum or near-optimum location for facilities. This feature facilitates easy visualization of the site planning process and encourages user participation. The model is structured in three main modules: Database, Project Module, and Layout Control Module. The functionality of each module, along with their interconnectivity is described. The model is implemented using Visual Basic for Applications in AutoCAD environment and Microsoft Access. A numerical example of an actual site layout is presented to illustrate the functionality of the developed model.