A linear‐discrete scheduling model for the resource‐constrained project scheduling problem

For some specific types of construction projects, the classical CPM or PDM scheduling techniques are not the most suitable. Few specific scheduling approaches have been developed to cope with construction projects that are made of either repetitive activities or activities with linear developments. But real‐world construction projects do not consist only of such activities. They are generally made of a mixture of linear and/or repetitive activities and of more conventional activities. To allow this, the linear scheduling problem is reformulated, so classical schedule calculation approaches can be used. The implementation of some Allen's algebra features to avoid adverse discontinuities and to allow crew/work continuity, together with a resource‐driven and space‐constrained scheduling are among the key features of the proposed approach. It is also a spin‐off of off‐the‐field practices used for scheduling real projects in the particle accelerator construction domain; an excerpt from such a construction project is provided for illustrating the methodology.     

Resource-driven scheduling of repetitive activities

Repetitive activities are found commonly in the construction of high-rise buildings, pipeline networks and highway and housing projects. Construction crews assigned to these activities often perform the work sequentially, moving from one repetitive unit in the project to the next. Because of this frequent crew movement, construction of repetitive activities should be scheduled in such a way as to enable prompt movement of crews among the repetitive units so as to minimize idle crew time. In order to maximize the efficiency of crew utilization, the schedule of repetitive activities should be resource driven, and should satisfy the crew work continuity constraint in addition to precedence relationships and crew availability constraints. This paper presents a flexible algorithm for resource-driven scheduling of repetitive activities that satisfies the three constraints, and considers the impact of a number of practical factors encountered commonly during the construction of this class of projects. The algorithm is applied in two stages: the first achieves compliance with logical precedence relationships and crew availability constraints, and the second achieves compliance with the crew work continuity constraint. A numerical example of a highway project is analysed to illustrate the use of the algorithm and demonstrate its capabilities.     

A genetic algorithm-based method for scheduling repetitive construction projects

This paper develops a new method for scheduling repetitive construction projects with several objectives such as project duration, project cost, or both of them. The method deals with constraints of precedence relationships between activities, and constraints of resource work continuity. The method considers different attributes of activities (such as activities which allow or do not allow interruptions), and different relationships between direct costs and durations for activities (such as linear, non-linear, continuous, or discrete relationship) to provide a satisfactory schedule. In order to minimize the mentioned objectives, the proposed method finds a set of suitable durations for activities by genetic algorithm, and then determines the suitable start times of these activities by a scheduling algorithm. The bridge construction example from literature is analyzed to validate the proposed method, and another example is also given to illustrate its new capability in project planning.     

System development for non-unit based repetitive project scheduling

Repetitive activities are commonly found in construction projects. It is stated in many literatures that repetitive scheduling methods are more effective than traditional CPM methods in the planning and scheduling of repetitive construction projects. Nevertheless, almost all the repetitive scheduling methods developed so far have been based on the premise that a repetitive project is comprised of many identical production units. In this research a non-unit based algorithm and a prototype system are developed for the planning and scheduling of repetitive projects. Instead of repetitive production units, repetitive or similar activity groups are identified and employed for scheduling. The developed system takes into consideration (1) the logical relationship of activity groups in a repetitive project, (2) the usage of various resource crews in an activity group, (3) the maintaining of resource continuity, and (4) the time and cost for the routing of resource crews. A sample case study is conducted for system validation, as well as for demonstration. Application of repetitive scheduling methods can be facilitated with the developed system.     

Optimized acceleration of repetitive construction projects

Contractors and/or owners frequently need to accelerate the delivery of construction projects. Contractors may have to accelerate in order to benefit from contractual bonus, avoid penalties, recover from delays and/or avoid undesirable weather and site conditions. Owners, on the other hand, may order acceleration to meat business and operational opportunities. This paper presents an algorithm for schedule updating, dynamic rescheduling and optimized acceleration of repetitive construction projects. Schedule updating captures the exact progress on site. Dynamic rescheduling aims at capitalizing on the repetitive nature of the project to fine-tune the remaining portion of the project. Optimized acceleration presents an optimized time–cost trade-off that is tailored for repetitive projects. Through a set of iterative steps, the optimized acceleration procedure divides each activity into segments and identifies the segments that would shorten project duration if accelerated. For those identified segments, the ones with the least cost slope are selected and queued for acceleration. Through the proposed segmentation of activities this algorithm provides optimum allocation of additional acceleration resources, thus is rendered capable of identifying least cost acceleration plans. The algorithm allows users to select among different acceleration strategies such as working overtime, working double shifts, working weekends, and employing more productive crews. The presented algorithm maintains work continuity and accounts for typical and non-typical activities. The algorithm is implemented in a spreadsheet application, which automates calculations, yet allows users to fine tune the algorithm to fit the project at hand. The developed algorithm is applied to a case study drawn from literature in order to illustrate its basic features and demonstrate its accuracy.     

Minimizing duration and crew work interruptions of repetitive construction projects

This paper presents the development of a novel scheduling model for minimizing the duration and crew work interruptions of repetitive construction projects. The main contributions of the developed model are its ability to (1) generate early and late start schedules that minimize the duration of repetitive construction projects while keeping the total work interruptions of their utilized crews to a minimum; (2) calculate novel types of crew work-continuity floats that consider the impact of delaying the early start of repetitive activities on crew work continuity; (3) develop a wide range of intermediate schedules between the early and late start schedules that maintain the least project duration and minimum total crew work interruptions; and (4) compare shortest duration schedules with and without interruptions to identify the best schedule that fits the specific project needs. The model performance was evaluated using an application example of a repetitive construction project.     

A multi-objective GA-based optimisation for holistic Manufacturing,transportation and Assembly of precast construction

Resource scheduling of construction proposals allows project managers to assess resource requirements, provide costs and analyse potential delays. The Manufacturing, transportation and Assembly (MtA) sectors of precast construction projects are strongly linked, but considered separately during the scheduling phase. However, it is important to evaluate the cost and time impacts of consequential decisions from manufacturing up to assembly. In this paper, a multi-objective Genetic Algorithm-based (GA-based) searching technique is proposed to solve unified MtA resource scheduling problems (which are equivalent to extended Flexible Job Shop Scheduling Problems). To the best of the authors' knowledge, this is the first time that a GA-based optimisation approach is applied to a holistic MtA problem with the aim of minimising time and cost while maximising safety. The model is evaluated and compared to other exact and non-exact models using instances from the literature and scenarios inspired from real precast constructions.     

Finance‐based CPM/LOB scheduling of projects with repetitive non‐serial activities

Projects of repetitive non‐serial activities constitute a major category of construction projects which can be scheduled more conveniently using the line of balance (LOB) technique. Generally, scheduling activities such that the expenditures are always in balance with the available cash is a must to devise financially feasible schedules. The objective is to integrate a CPM/LOB model for a project of repetitive non‐serial activities with a cash flow model and utilize the integrated model to devise financially feasible schedules. The genetic algorithms (GAs) technique is employed to maximize the profit at the end of the project under the constraints of available cash. The optimization of the integrated models was demonstrated using an example project of 15 activities carried out at five units. The CPM/LOB model was validated against the results of a dynamic programming model in the literature and further by conducting a sensitivity analysis of the results of the integrated model. Finally, the model offers an effective financial planning tool for projects of repetitive non‐serial activities.     

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.     

Optimizing project selection and scheduling problems with time-dependent resource constraints

This study presents an optimization model using constraint programming (CP) for project selection and scheduling problems with time-dependent resource constraints. A generic model is proposed to maximize the total profit of selected projects for construction and R&D departments given scheduling problems with various resource constraints during specified time intervals, including consumed and renewable resource limitations. Due to different periodical procurement strategies and annual budget concerns, this research considers various practical limitations for scheduling and allocating resources, such as budget limitations and resource constraints. For additional practicality, the optimization model integrates a project selection mechanism, scheduling precedence, and relationships between projects. To illustrate the model capabilities for solving project selection and scheduling problems, the current study presents two scenarios for maximizing profit, including fifteen candidate projects with time-dependent resource constraints. Analysis results demonstrate that the proposed model allows planners to determine an optimal portfolio with specified resource constraints according to various time intervals, and benefits decision-making for project selection and scheduling.     

Resource Leveling in Line‐of‐Balance Scheduling

Resource leveling involves minimizing resource fluctuations without changing the completion time of a project. A smooth distribution of resources minimizes logistical problems and results in cost savings. Line‐of‐balance (LOB) is a resource‐based scheduling system that is used in projects that exhibit repetitive characteristics, performs resource allocation as a matter of course, but does not deal with resource leveling. In the past, researchers experienced declines in productivity whenever they leveled resources in different linear scheduling models by adjusting activities’ production rates. The objective of this research is to develop a genetic algorithm‐based resource leveling model for LOB schedules that does not impact productivity negatively. This model is based on the “natural rhythm” principle, according to which a crew of optimum size will be able to complete an activity in the most productive way. The “natural rhythm” principle allows shifting the start time of an activity at different units by adjusting the number of crews without changing the duration of the activity in any one unit and without violating the precedence relationships between activities. An LOB schedule is established for a pipeline project and is used to illustrate the proposed resource leveling model. It was observed that the model provides a smoother resource utilization histogram. Performing resource leveling in LOB scheduling without sacrificing productivity is the major contribution of the proposed model.     

The determinants of the vertical boundaries of the construction firm: comment

A method is presented for allocating resources to construction activities and for scheduling construction projects under resource constraints by considering the effects that such resource limitations may have on the tendency of the activities (and the project in general) to fall into disarray and behind schedule. Resource‐constrained scheduling problems (RCSP) are very common in real‐life construction projects and because of their nature their numerical solution is computationally intensive. The method utilizes a measure of each activity's perceived level of disorder stemming from resource limitations. The proposed technique aims to optimize the number of resources assigned to the activities and to schedule the project so as to minimize the overall project's tendency to fall into disorder. The entropy‐like metric used in the scheduling optimization is related to the ratio of required over‐assigned resource units per activity, and its utilization allows a planner to take into consideration project disorder when planning a project. A case study and its mathematical framework help demonstrate the ‘duration vs. disorder’ trade‐off analysis that planners should perform when considering possible activity resource assignments and the feasibility of these assignments in terms of induced disorder. The entropy optimization method proves to be a powerful project‐planning metric.     

Two‐stage profit optimization model for linear scheduling problems considering cash flow

Linear projects with repetitive activity in units are considered for investigation, and a two‐stage profit optimization model for linear scheduling problems using constraint programming (CP) is proposed. To maintain work continuity for repetitive activities, interruption time and crew availability are addressed, and the optimization process is presented as follows: (1) optimizing the primary objective (project profit); (2) minimizing total interruption time, given the optimized value of the primary objective. Repetitive activities incur batches of budget expenditure according to activity implementation time. Cash flow and financial elements are therefore integrated into the optimization model. Owing to flexible CP techniques, contractors’ requirements, such as credit limit and payment conditions, can be integrated simply into the model formulation for practical use. Lastly, a bridge example is adopted, with various constraints such as duration limitation, for scenario analysis. Consequently, the two‐stage optimization process optimizes project profit, and also maximizes work continuity for linear scheduling problems.     

Resource-constrained scheduling for continuous repetitive projects with time-based production units

In construction projects of highways, pipelines, and tunnels, labor and equipment continuously move in a linear geographic layout. This class of continuous repetitive projects encounters the resource-constrained problem when there are limits on the availabilities of resources (labor and equipment). Conventional scheduling models divide continuous repetitive projects into space segments. The premise is that crews would maintain the same production rate in each space segment. However, when the length of segment is indivisible by the production rate, this assumption leads to an inefficient schedule which asks the crews to change their production rate, a reflection of their size, composition, and associated equipment, in the middle of a time period. Unproductive time would then be spent in extra preparation and unnecessary warming up. Another drawback is that production units divided in space cannot be directly linked to the time-based payment schedule. In light of these shortcomings, this paper presents a scheduling model to find the optimal set of production rates in different time periods for each crew, considering limited availability of resources. To be practical, the proposed model addresses work continuity while maintaining lead-time and lead-distance between operations. The optimization problem is solved by an evolutionary strategy algorithm, which is easy to program and takes less execution time, with no need for selection and crossover process. A real-life project is used to validate the performance of the proposed model in terms of effectiveness, efficiency, and stability.     

An innovative approach for generation of a time location plan in road construction projects

Existing linear scheduling methods for earthwork activities lack accurate scheduling locations in road construction projects. Project planners and construction managers largely depend on subjective decisions for the allocation of resources at correct locations. This has caused uncertainties in planning and scheduling, and consequently delays and cost overruns of projects. Accurate information of working locations is vital for efficient resource planning, scheduling and equipment mobilisation. A theoretical framework for a virtual construction prototype model is developed using the theory of location‐based planning and this is used as the basis of sensitivity analysis to identify critical factors affecting road construction. An arithmetic algorithm is developed by incorporating road design data, sectional quantities, variable productivity data, unit cost, site access points and haulage distance. The model generates a time location plan automatically with the aim to provide location‐based scheduling information of earthwork activities. Weekly progress profiles, terrain surfaces, cost profiles and S‐curve are the other outputs of the model. Data and information collected from the case studies are used to demonstrate functionalities of the model. Critical factors controlling the productivity of earthwork activities such as different types of equipment, soil characteristics and site access points were used to display the sensitivity effect by means of ‘what‐if scenarios’. The model is a valuable tool in analysing impacts of different factors associated with productivity data and resource planning from location aspects in the earthwork construction projects.     

地下工程施工突发事件应急辐射研究

地下工程施工突发事件破坏程度高,单靠项目部的应急救援能力,往往不足以应对。阐明了地下工程施工突发事件应急辐射的作用,指出应急辐射具有时效、差异、动态、双向等特点,研究分析了影响应急辐射的应急救援力量、应急资源、专业救援匹配度、应急处置效率、交通运输条件等5种因素,构建了地下工程施工突发事件应急辐射模型,并进行实证研究。研究表明:施工企业和项目部应科学评估周边应急辐射强弱,充分利用附近的应急救援力量和资源,与自身的应急准备互为补充,共同应对重特大施工突发事件,能够有效减少自身的应急准备投入,提高资源配置效率。     

Simulating the impacts of policy scenarios on the sustainability performance of infrastructure projects

Sustainable development principles have been implemented in various sectors including the construction industry since it was published in the Brundtland Commission Report in 1987. In line with this development, implementation of infrastructure construction projects has been given particular attention as they have more significant impacts on the environment, society and economy. It is considered that proper development and operation of infrastructure projects such as highways can contribute significantly to the mission of sustainable development. However, there is little existing work to provide appropriate methods to assess the sustainability performance of infrastructure projects. The study described in this paper introduces a simulation model, using system dynamics principle, to evaluate the sustainability performance of highway infrastructure projects during the construction and operation stage. The study introduces the indicators which measure the sustainability performance of highway projects and identifies the dynamic factors affecting indicator performance by referring to the relevant feasibility studies of highway projects. A real highway project is presented to demonstrate the application of the simulation model in evaluating the sustainability performance of the project. The case study is used to explore the solutions for improving those poor sustainability performance areas through policy scenarios.     

作业成本法在水电工程施工企业中的应用

通过对工程施工项目的工程特点、施工环境等因素的分析,结合施工计划,确定施工作业类型和各作业中所需要的资源种类,然后进行资源配置,确定资源数量,估算作业生产率和作业持续时间,进而根据资源的使用持续时间和单位时间消耗的费用来计算作业成本。以此估算的工程造价能够较准确地反映工程成本。     

Resource scheduling and planning for tunneling with a new resource model of the Decision Aids for Tunneling (DAT)

Resource scheduling and planning are the strategies required to determine the sequence of activities and resource allocation during tunnel construction. Resource scheduling and planning have been implemented in a new resource model of the Decision Aids for Tunneling (DAT), which are a computer based tool used to simulate tunnel construction. Tunneling plans obtained with the new resource model of the DAT take into account the technical precedence of activities, the resource/space availability, the dynamic status of the process, and the work continuity. In particular, the new resource model of the DAT can provide the optimal tunneling plan, which produces the shortest construction time and the smallest construction cost, and satisfies the special characteristics of tunnel construction such as excavation methods, distance requirements between the headings, and preempting activities (e.g., blasting).The paper attempts to contribute to both theory and practice: Optimization of the construction process considering time, cost and resources is particularly complicated in tunneling where activities and resource availability have to be appropriately sequenced and interference has to be avoided. The paper addresses this fundamental problem with the development of different schematic tunneling plans that consider the relevant activities and optimizes them with regard to overall cost and time, also considering uncertainties. Equally important is to make the theoretical development practically useable. This is done through implementation of the resource optimization in the DAT and, very importantly, by demonstrating the practical use with an application to a real tunnel case.     

Uncertainty Processing and Risk Monitoring in Construction Projects Using Hierarchical Probabilistic Relational Models

Construction projects do not often reach their expected results regarding time, cost, and quality, due to the internal and external environment variations. Despite a substantial literature about risk management, no generic approach is proposed to represent construction project considering together technical and human dimensions or sustainability with their uncertainties. Modeling complex dynamical systems from heterogeneous pieces of knowledge varying in precision and reliability is a challenging task. This article proposes an innovative generic and versatile approach, based on the formalism of hierarchical probabilistic relational models to analyze and to propagate uncertainty in construction project regarding different levels of knowledge. The aim is to obtain a flexible, portable, and versatile model able to simulate the behavior of complex system's entities involved in any construction project at different levels of detail while taking uncertainty into account. To illustrate and highlight this approach, an academic example and a real case are proposed.