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.     

A framework of critical resource chain for project schedule analysis

Analysing a schedule is beneficial to help stakeholders understand the scheduled project. Project schedules, which create time plans based on the critical path method (CPM) or on resource‐constrained project scheduling problem (RCPSP) optimization, are targets herein. The Theory of Constraints (TOC) treats a schedule as a system. Schedule elements are suspected constraints and a goal depends on the schedule creation policy. Resource information is further surveyed herein to identify true constraints. A framework is proposed to integrate identified constraints on a schedule, and the critical resource chain concept is introduced. Three scenarios illustrate the proposed framework under different scheduling considerations. Results explain schedule constraints, and several schedule analysis issues are discussed.     

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.     

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.     

CPM/LOB Scheduling Method for Project Deadline Constraint Satisfaction

This paper presents a methodology to improve CPM/LOB scheduling method for deadline constraint satisfaction. A complete and simple heuristic approach called “heuristic line of balance” (HLOB) is introduced for scheduling projects with serial activities. It employs four heuristic rules and their appropriate combination in addition to seeking CPM/LOB initial calculation. As an improvement to the HLOB algorithm, the “search-based heuristic line of balance” (SHLOB) algorithm is also presented, which is more efficient as projects grow in size. Finally, a complete mathematical version of the LOB model in the form of mixed integer nonlinear programming (MINLP) is applied for verification of the proposed models. Two simple case studies and a hypothetical large-scale highway project are used to test the performance of the improved models. Due to the results of this paper, HLOB and SHLOB are able to present optimum/near optimum solutions in a much more economical way that may justify their widespread use.     

Multi-mode resource-constrained discrete time–cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm

Minimizing both project time and cost is an important matter in today's competitive environment. Therefore trade-off between project time and cost is necessary. In projects, each activity can be started at different time points, depending on its precedence relationship and resource availability. Also cost and duration of the activities could be changed depending on the allocated resources. In addition, another strategy that affects the project total time and cost is resource leveling, which is applied to reduce excessive fluctuations in the resource usage. In this paper multi-mode resource-constrained project scheduling problem (MRCPSP), discrete time–cost trade-off problem (DTCTP) and also resource allocation and resource leveling problem (RLP) are considered simultaneously. This paper presents the multi-mode resource-constrained discrete time–cost-resource optimization (MRC-DTCRO) model in order to select starting the time and the execution mode of each activity satisfying all the project constraints. To solve these problems, non-domination based genetic algorithm (NSGA-II) is employed to search for the non-dominated solutions considering total project time, cost, and resources moment deviation as three objectives. The results of MRC-DTCRO model presented in this paper show that adding the resource leveling capability to the previously developed multi-mode resource-constrained discrete time–cost trade-off problem (MRC-DTCTP) models provides more practical solutions in terms of resource allocation and leveling, which makes this research applicable to both construction industry and researchers.     

Resource constrained project scheduling using simulation

Resource allocation is one of the most important issues of construction management. Two problems of resource allocation are of concern: resource levelling and resource scheduling. Traditionally, the resource scheduling problem is solved using either heuristic methods or optimization techniques. When heuristic methods are used, resource scheduling is treated as a subsequent problem for the CPM analysis. In this paper, the resource scheduling problem is handled using simulation, where logic dependence and resource availability limits are considered simultaneously during the time scheduling process. Simulation is applied to the resource scheduling problem at the project level. A simulation system called SIRBUS is used to schedule construction projects under resource constraints. Constant resource demand of activities is assumed, and the activity once started cannot be interrupted. Six example projects previously solved by different heuristic methods are re-solved using simulation. The results are compared with the latest heuristic models: current float technique and ranked positional weight method. In addition to the advantage that resource availability is considered during time scheduling as a starting point, which is an apparent feature of simulation, SIRBUS gives good results compared with existing heuristic methods.     

BIM-based integrated approach for detailed construction scheduling under resource constraints

Building information modeling (BIM) has been recognized as an information technology with the potential to markedly change the Architecture, Engineering, and Construction (AEC) industry, and has drawn attention from numerous scholars within the construction domain. Despite the reported advancements pertaining to BIM in previous studies, the extended use of BIM has not yet reached its full potential. This paper thus presents a BIM-based integrated scheduling approach which facilitates the automatic generation of optimized activity-level construction schedules for building projects under resource constraints, by achieving an in-depth integration of BIM product models with work package information, process simulations, and optimization algorithms. A developed prototype system for panelized building construction as an add-on tool for Autodesk Revit is described. A case study is subsequently presented to demonstrate the methodology. Building on the existing body of research in this field, the key contribution of the proposed research is the in-depth integration of BIM product model with work package information, process simulations, and an optimization model, which provides solutions addressing the challenges of the existing practice with respect to detailed construction scheduling under resource constraints.     

Schedule control model for linear projects based on linear scheduling method and constraint programming

China Railway is undertaking massive construction and development projects.A reasonable and resource-leveled schedule that allows for adjustments for unforeseen circumstances during construction is critical for managing railway construction projects. Currently, most construction projects use traditional network planning methods or the Gantt schedule for project management. However, these methods have limited applicability to railway construction projects, which are typically linear. This study uses the linear scheduling method and constraint programming techniques for solving schedule control problems faced during railroad construction. The proposal comprises a schedule control model, scheduling model, and schedule control system; the scheduling model is central to the schedule control model. Characteristics such as high flexibility and practicality facilitate multi-objective optimization during scheduling and modification of the linear schedule. The proposed model and algorithm were validated by comparing results with actual data from a highway construction project and the Urumqi–Dzungaria railway construction project.     

不确定性条件下建设工程设计进度优化研究

随着建设工程项目的大型化、复杂化,其设计中的迭代问题也呈多发趋势。但相应技术或方法的缺乏,使得管理者在面对此类问题时常显得束手无策。因此,本文尝试将DSM理论引入到复杂建设工程设计进度管理领域,针对传统进度管理方法的缺陷及现有复杂建设工程设计过程中易发的迭代问题,构建一种以DSM理论为基础的进度优化体系,同时用蒙特卡洛模拟方法对设计进度的不确定性进行研究,最终将其运用于某大飞机配套工程设计进度优化中。结果显示,该模型在迭代活动识别、活动排序优化及工期分布预测计算方面均具有一定的优势,并可以通过解耦操作实现进度的优化,通过仿真模拟预判关键活动,为复杂建设工程设计进度的优化提供了新的思路。     

用于道路施工进度计划分包与调度优化的改进异构环境最早结束时间算法

大型道路工程需要合理的任务分包与调度。在实际中, 施工进度任务的调度与可用的施工资源组是密切相关的, 然而不同施工资源组对相同任务的执行能力往往各不相同(即资源系统异构), 这一重要特点为已有的研究所忽略。本文首先提出一个新的算法Modified Heterogeneous Earliest Finish Time(MHEFT), 该算法基于构建的施工进度计划DAG模型与异构资源系统模型来优化异构资源环境下道路施工进度计划; 然后使用上海市南翔大型社区陈翔路工程的实际数据进行模拟实验, 实验结果表明该算法在减少施工工期方面十分有效; 此外, 本文还通过扩展实验证明了该算法鲁棒性优越。     

建设项目多目标综合优化方法研究

对于工程的质量、工期、成本、资源的均衡等多个目标进行控制市建筑工程项目管理的重要内容。在具体分析各个目标之间相互作用关系的基础上,建立了工期-费用关系模型、质量工期关系模型和资源均衡-工期关系模型。进一步在工程费用-费用优化的基础上,引入工程质量、资源均衡目标,综合单目标模型,建立了进度计划的多目标模型,利用多目标模糊决策理论,对实施方案进行优选,最后用算例验证了方法的可行性和实用性。     

Modeling the supply chain configuration problem with resource constraints

In this paper, we study the supply chain configuration problem (SCCP) under resource constraints. We present a new modeling framework based on multi-mode resource-constrained project scheduling (MRCPSP) for configuring the supply chain subject to explicit resource constraints. It establishes a bridge between the areas of project scheduling and supply chain design. Our model is also able to handle additional practical issues such as quality level requirements and general temporal constraints, which are often encountered in the real world. A constraint programming (CP) based solution approach is proposed and implemented in our case study. Conclusions and future research directions are discussed.     

基于微粒群算法的工程项目资源均衡优化

将微粒群算法运用到工程项目管理的资源均衡优化问题,定义了以活动的实际开始时间作为微粒坐标的微粒群;建立了资源方差与活动实际开始时间直接联系的评价函数;通过微粒群在飞行中位置的进化过程来搜索对应于最优方案的活动实际开始时间。最后通过算例的计算分析,用微粒群算法得到的资源强度比初始方案降低了75.2%,比遗传算法的结果降低了26.97%,验证了该方法在工程项目管理的资源均衡优化中的可行性及有效性,同时还获得了若干个次优方案,对于工程项目管理中的资源均衡优化具有实际应用价值。     

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.     

Optimizing schedule for improving the traffic impact of work zone on roads

Many different types of construction projects set up work zones on roads. Especially in urban areas, lane closures as a result of work zones have a considerable impact on local traffic. However, for a construction project that consists of several work zones and several work crews, the traffic impact may be improved by appropriate scheduling. Therefore, this paper proposed a scheduling model based on the route-changing behavior of road users. The proposed model calculates the traffic delay of vehicles by microscopic simulation, and applies team ant colony optimization to search for a near-optimal schedule. The project planner then ensures that the contractor executes the activities according to the near-optimal schedule. The proposed model is applied to schedule a sewer system construction project in a city. The results of our study indicate that with our proposed model the total traffic delay is reduced by 11.1% when compared with a schedule proposed by the project planner.     

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.