Resource Optimization Using Combined Simulation and Genetic Algorithms

This paper presents a new approach for resource optimization by combining a flow-chart based simulation tool with a powerful genetic optimization procedure. The proposed approach determines the least costly, and most productive, amount of resources that achieve the highest benefit/cost ratio in individual construction operations. To further incorporate resource optimization into construction planning, various genetic algorithms (GA)-optimized simulation models are integrated with commonly used project management software. Accordingly, these models are activated from within the scheduling software to optimize the plan. The result is a hierarchical work-breakdown-structure tied to GA-optimized simulation models. Various optimization experiments with a prototype system on two case studies revealed its ability to optimize resources within the real-life constraints set in the simulation models. The prototype is easy to use and can be used on large size projects. Based on this research, computer simulation and genetic algorithms can be an effective combination with great potential for improving productivity and saving construction time and cost.     

Particle Swarm Optimization-Supported Simulation for Construction Operations

This study proposes an integration of particle swarm optimization (PSO) and a construction simulation so as to determine efficiently the optimal resource combination for a construction operation. The particle-flying mechanism is utilized to guide the search process for the PSO-supported simulation optimization. A statistics method, i.e., multiple-comparison procedure, is adopted to compare the random output performances resulting from the stochastic simulation model so as to rank the alternatives (i.e., particle-represented resource combinations) during the search process. The indifference zone and confidence interval facilitate consideration of the secondary performance measure (e.g., productivity) when the main performance measures (e.g., cost) of the competing alternatives are close. The experimental analyses demonstrate the effectiveness and efficiency of the proposed simulation optimization. The study aims to providing an alternative combination of optimization methodology and general construction simulation by utilizing PSO and a statistics method so as to improve the efficiency of simulation in planning construction operations.     

Integrated Reservoir-Based Canal Irrigation Model. II: Application

In a companion paper, development of an integrated reservoir-based canal irrigation model (IRCIM) was described. This developed model combines catchment hydrological modeling, reservoir water balance, command hydrological modeling, and a simple canal hydraulic simulation through a rotational irrigation management system, and simulates the whole system as a single unit to ensure equitable distribution of supply to meet the demand if possible, or, to minimize the gap between the supply and demand. In this paper, the developed model was applied to Kangsabati Irrigation Project, West Bengal, India, as a case study. Results showed that IRCIM successfully simulated the operation of the test reservoir after proper calibration and was able to determine better delivery schedules than that actually practiced. The best delivery schedule determined by IRCIM improved the performance of the test irrigation project considerably over the actual delivery schedule for most of the simulation years. Based on these yearly results, a year-independent alternative delivery schedule was also proposed which could be followed mechanically without a manager’s expertise or experience on the particular irrigation project. It was also shown that IRCIM could be used successfully both modulewise or in an integrated way depending on the requirement of the irrigation manager for efficient operation of any reservoir-based canal irrigation systems either for preseason planning of allocation schedules based on hydrologic and hydraulic simulations or for postseason evaluation of the system performance.     

Productivity Analysis of Construction Operations

An interactive system for analysis of construction operations is proposed. The analysis is carried out in the context of various work modules which address quantity development, resource definition, and production and cost analysis. The quantity work module generates quantities based on information available in the design documents. The resource definition module receives and stores data regarding the labor∕equipment combination to be used to execute work tasks. This module provides the user with a set of standard useful construction process models. For each construction operation to be analyzed, the terminal describes the standard models. The user makes input of a set of parameters for process keyname, quantity, work task durations, number of resources, production capacity of each unit, and cost per hour of each unit to the standard model to be used. Using input from the resource definition module, the productivity and cost analysis module generates production rates and unit costs based on process simulation using CYCLONE methodology.     

Resource Management of Bridge Deck Rehabilitation: Jacques Cartier Bridge Case Study

The condition and performance of bridges vary widely across North America. The large amount of expenditures on bridges needs significant efforts to optimize budget and resource allocation and to select the best rehabilitation or replacement method, which reduces project cost and duration. Simulation has been widely used in the construction area to optimize productivity and resource allocation. Current research optimizes resource combination for bridge deck rehabilitation projects using discrete event simulation. The Jacques Cartier Bridge redecking project is selected as a case study. Data related to productivity and duration of different activities were collected from the project. Probability distributions are fitted, which show the robustness of normal distribution to fit most variables. A simulation model is developed for this project in order to experiment with and perform sensitivity analysis. Based on the simulation results, an optimum resource combination of deck rehabilitation is obtained, which is [five teams, two saws, three old section trucks, and five new panel trucks] TSON 5235 with the unit (panel) cost of $747/h (direct cost only). The model developed is tested against real productivity where it shows reasonable results. The present research is relevant to both researchers and practitioners. It provides bridge redecking researchers with a real case study, a simulation model, and an approach to analyze projects. It also provides practitioners with an approach to optimize the usage of their resources considering direct project cost.     

Linear Programming Approach to Optimize Strategic Investment in the Construction Workforce

The construction industry in the United States and other parts of the world has been facing several challenges, including a shortage of skilled workers. A review of the relevant body of knowledge indicates that one of the key reasons for this problem is the absence of human resource management strategies for construction workers at project, corporate, regional, or industry levels. This paper addresses the issues of workforce training and allocation on construction projects. It presents a framework to optimize the investment in, and to make the best use of, the available workforce with the intent to reduce project costs and improve schedule performance. A linear program model, entitled the Optimal Workforce Investment Model, is built to provide an optimization-based framework for matching supply and demand of construction labor most efficiently through training, recruitment, and allocation. Given a project schedule or demand profile and the available pool of workers, the suggested model provides human resource managers a combined strategy for training the available workers and hiring additional workers. The input data to the proposed model consists of a certain available labor pool, cost figures for training workers in different skills, the cost of hiring workers, hourly labor wages, and estimates of affinities between the different considered skills. The objective of the model is to minimize labor costs while satisfying project labor demands. Results from application of the model to typical situations are presented, and recommendations for future developments are made.     

Simulation-Based Schedule Estimation Model for ACS-Based Core Wall Construction of High-Rise Building

Many existing studies about construction schedule management focus on the planning phase of a project, particularly on schedule estimation based on the labor resources involved in the project. However, equipment resources, which are another crucial factor in the productivity of a construction project, have not been considered in existing research. Therefore, this study aimed to develop a schedule estimation model considering both labor and equipment resources. For the purpose of this study, core wall construction was selected because it is a very important construction activity in terms of schedule estimation for high-rise building construction. To develop a schedule estimation model for core wall construction, an in-depth case study was conducted. On the basis of the results of the case study, a simulation model was developed using the CYCLONE method. Finally, by using the results of the simulation, a schedule estimation model for core wall construction was developed by conducting multiple-regression analysis. By using the developed model, a project manager can easily, quickly, and accurately perform schedule estimation when there are problems that may cause construction schedule delays during the construction phase.     

Integrating Efficient Resource Optimization and Linear Schedule Analysis with Singularity Functions

Resources perform or enable physical operations and thus are vital on construction projects, yet are subject to various constraints. Their use within a project schedule must therefore be carefully planned. A major objective is optimizing when they are active within the float of noncritical activities to avoid disruptive and costly fluctuations. This paper builds on analyzing criticality of linear schedules with the unique singularity functions. The new approach keeps resources intact and derives one flexible equation for the complete resource profile of a schedule, including any timing or resource rate changes. Another equation models its first moment of area to minimize the objective function toward a level profile. A genetic algorithm is suitable for an iterative optimization. The parameters of its chromosomes are recombined evolutionarily and can model any permutation. Analyzing a road project illustrates how singularity functions integrate resource optimization with its linear schedule and facilitate a subsequent optimization.     

Integrated Schedule and Cost Model for Repetitive Construction Process

Several efforts have been made by many researchers to develop a model for schedule and cost integration in construction projects, but it is difficult to integrate and manage schedule and cost in an actual construction site using such a model. The integrated schedule and cost model developed in this study (1) enables the planning and control of repetitive construction processes and (2) can be used by a project manager in an actual construction site. Furthermore, an integrated schedule and cost model for the core wall construction, which is an important repetitive process in the recently booming high-rise building construction in terms of scheduling, was developed using the integration model developed in this study. It is expected that the integrated schedule and cost model developed can allow project managers to integrate the schedule and cost of repetitive construction processes more effectively and support the project managers’ decision-making.     

Simulation of Concrete Paving Operations on Interstate-74

The objective of this paper was to study and optimize the concrete paving operations taking place in the reconstruction project of Interstate-74 using computer simulation. To achieve this objective, field data were collected during construction, and were then used to determine adequate probabilistic density functions for the activities’ duration and to test a developed simulation model. Upon testing, the developed model was used to study the impacts of resources on the flow of operations and on the cost effectiveness of the construction process. In general, application of simulation methods to concrete paving operations was successful and its accuracy was acceptable as compared to field measurements. Based on the results of a sensitivity analysis of the critical resources, multiple factors were considered in the decision-making process to ensure that all aspects of the operation are evaluated. This includes total operation time, productivity, costs of the operation, average truck delay, and idle times for the paver and the spreader. For the conditions pertinent to this construction site, ten trucks, one paver and one spreader, and three finishing and plastic-covering crews are recommended. Using this set of resources would result in a prompt and effective execution of the operation. Practical implementation and limitations of the developed model in similar construction operations is discussed.     

Materials Handling System Simulation in Precast Viaduct Construction: Modeling, Analysis, and Implementation

The interactive, complicated system environment of a construction site renders conventional site layout planning and scheduling techniques to be inadequate in coping with materials handling system design in construction. In this paper, we present a university-industry joint endeavor for improving the effectiveness of the materials handling system on a precast viaduct construction project in Hong Kong by implementing the simplified discrete-event simulation approach (SDESA) along with its computer platform resulting from recent research. How to apply the simulation methodology of SDESA is elaborated step by step. Particular emphasis is placed on procedures of establishing a simulation model, validation of the simulation model, design of simulation experiments, and analysis of simulation results. With process flowchart, site layout plan, and process animation produced in a view-centric simulation environment, it is straightforward to establish, validate, and communicate the operations simulation. The research team convinced the project director, as well as field managers, of the functionality and effectiveness of operations simulation. The knowledge derived from simulation added to experiences of site managers in materials handling system design. With the aid of simulation, even junior engineers would be capable and confident to draw up an actionable construction plan that would lead to enhancement of cost effectiveness and productivity in the field.     

Simulation Approach to Evaluating Cost Efficiency of Selective Demolition Practices: Case of Hong Kong’s Kai Tak Airport Demolition

This research resorted to the use of construction operations simulation modeling to investigate the cost efficiency of waste-handling practices on the Kai Tak Airport demolition project in Hong Kong. By modeling the site operation of sieving and stockpiling broken concrete, the well-established construction simulation methodology of CYCLONE was contrasted with the newly developed simplified discrete event simulation approach (SDESA). Further, the SDESA model was readily extended to include (1) raw demolition waste collecting and sorting; (2) broken concrete sieving and stockpiling; (3) steel bar recycling; and (4) debris disposal at the landfill. The production rate derived from simulation was indicative of a close match between the simulation model and the actual site system. The resulting simulation model provided a basis for evaluating the cost efficiency of actual site operations and alternative resource provision scenarios being postulated. Through computer simulation, the actual site operation was found smooth and efficient with utilization rates for resources of different types ranging from 79 to 99%. In addition, the cost–time reduction ratios were calculated for four alternatives of resource provisions in comparison with the original base case. The research findings suggested that provided the project budget had satisfied the higher cash flow requirement, doubling the resource provision on site would potentially cut the project duration by half and not increase the total direct cost.     

Case Study on the Evaluation of Equipment Flow at a Construction Site

The purpose of this study is to evaluate the effects of traffic flow of construction equipment. A large construction project requires large quantities of construction equipment. This volume can result in traffic congestion in the flow of construction equipment, which also lowers the overall efficiency of construction operations. In particular, this effect can be serious in the area where traffic bottlenecks are most likely. This study applies a multiagent-based simulation modeling approach to a real project. Through a case study, this study evaluates how traffic flow of construction equipment influences the efficiency of that equipment in construction operations and, moreover, the schedule of a project.     

RISim: Resource-Interacted Simulation Modeling in Construction

Discrete-event simulation is an effective approach to analyze construction operations. However, it is usually time-consuming and knowledge demanding to develop a practical simulation model, and thus not cost-effective due to the uniqueness and relatively short life of construction projects. The capability of discrete-event simulation modeling has not been popularly recognized by site managers until recently. A clear and explicit solution is to simplify and speed up the model development cycle, so as to enable users without much knowledge of simulation technology to easily generate a model in a relatively short period of time. In this paper, a resource-interacted simulation (RISim) modeling approach is presented, which adopts a resource oriented methodology to promote an intuitive feel to simulation modeling. In RISim, an operation is modeled in two abstraction levels—namely, the resource level and process level. An operation is viewed as a collection of resources and their interactions. Complex resources and simple resources are used to respectively represent resources with or without their own processes. The operation logic is mainly represented with internal complex resource flows, which are integrated by simple resource flows between complex resources. Resource flows can be easily conceived by site managers, enabling them to build up the logic naturally and simply. A resource library is used to implement resource reusability. Finally, an example in concrete delivery operation illustrates the methodology of resource-interacted simulation modeling and its potential for “plug-in and simulate.”     

Parade Game: Impact of Work Flow Variability on Trade Performance

The Parade Game illustrates the impact work flow variability has on the performance of construction trades and their successors. The game consists of simulating a construction process in which resources produced by one trade are prerequisite to work performed by the next trade. Production-level detail, describing resources being passed from one trade to the next, illustrates that throughput will be reduced, project completion delayed, and waste increased by variations in flow. The game shows that it is possible to reduce waste and shorten project duration by reducing the variability in work flow between trades. Basic production management concepts are thus applied to construction management. They highlight two shortcomings of using the critical-path method for field-level planning: The critical-path method makes modeling the dependence of ongoing activities between trades or with operations unwieldy and it does not explicitly represent variability. The Parade Game can be played in a classroom setting either by hand or using a computer. Computer simulation enables students to experiment with numerous alternatives to sharpen their intuition regarding variability, process throughput, buffers, productivity, and crew sizing. Managers interested in schedule compression will benefit from understanding work flow variability's impact on succeeding trade performance.     

Quantifying the Impact of Schedule Compression on Labor Productivity for Mechanical and Sheet Metal Contractor

In a typical construction project, a contractor may often find that the time originally allotted to perform the work has been severely reduced. The reduction of time available to complete a project is commonly known throughout the construction industry as schedule compression. Schedule compression negatively impacts labor productivity and consequently becomes a source of dispute between owners and contractors. This paper examines how schedule compression affects construction labor productivity and provides a model quantifying the impact of schedule compression on labor productivity based on data collected from 66 mechanical and 37 sheet metal projects across the United States. The model can be used in a proactive manner to reduce productivity losses by managing the factors affecting productivity under the situation of schedule compression. Another useful application of the model is its use as a litigation avoidance tool after the completion of a project.     

Adaptive Control for Safe and Quality Rebar Fabrication

Rebar fabrication is a labor intensive operation that uses scrap or “trash” steel for raw materials and therefore can benefit greatly from improvements in safety, productivity, and quality. Shared control through a human-machine interface may be the best alternative for achieving highest quality standards and improving worker performance in safety and productivity. This paper develops a control scheme for automated rebar bending within the framework of computer integrated construction and presents research focused on the task level control to compensate for springback in the bent rebar. Three major problems are addressed: (1) Conception of a hierarchical computer integrated construction control structure that links rebar fabrication to the other construction project functions: (2) comparative evaluation of alternative algorithms for prediction of springback; and (3) portability of a springback control model that uses real-time electronic sensing. Bending tests were conducted with both a laboratory prototype and an actual shop table bender to experiment with alternative models for in-process springback prediction including a neural network model. Limitations in control system portability were realized in the transfer from the laboratory prototype bender to the shop bender. Springback model evaluations revealed that empirical statistical models, neural networks, and in-process relaxation performed equally well.     

Measuring and Modeling Labor Productivity Using Historical Data

Labor productivity is a fundamental piece of information for estimating and scheduling a construction project. The current practice of labor productivity estimation relies primarily on either published productivity data or an individual’s experience. There is a lack of a systematic approach to measuring and estimating labor productivity. Although historical project data hold important predictive productivity information, the lack of a consistent productivity measurement system and the low quality of historical data may prevent a meaningful analysis of labor productivity. In response to these problems, this paper presents an approach to measuring productivity, collecting historical data, and developing productivity models using historical data. This methodology is applied to model steel drafting and fabrication productivities. First, a consistent labor productivity measurement system was defined for steel drafting and shop fabrication activities. Second, a data acquisition system was developed to collect labor productivity data from past and current projects. Finally, the collected productivity data were used to develop labor productivity models using such techniques as artificial neural network and discrete-event simulation. These productivity models were developed and validated using actual data collected from a steel fabrication company.     

Model based optimisation of highly automated industrial batch annealing operation

Abstract

Modern batch annealing operations are highly automated facilities, equipped with online sensors, model based control and a production management system to archive material, process and quality parameters. In these operations, efficient models and algorithms are used to allocate the resources, schedule the operation and design process cycles of individual stacks. The present work endeavours to enhance the productivity of a highly automated batch annealing facility, operating well above its rated capacity. This was achieved by intelligent analysis of production data and a critical assessment of the prevalent thermal model used for designing the process cycle of the individual stack. Two major limitations, namely, the inability to capture non-isothermal kinetics and the stiff radial conductivity model, of the prevalent thermal model were identified. These limitations were eliminated by designing process cycles with an integrated process model, where phase transformation kinetics is incorporated. Implementation of these process cycles has enhanced the productivity of the batch annealing operation by 7–9%. These benefits have been validated through rigorous laboratory experiments and plant trials.