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Abstract: This study investigated resource leveling problems concerning linear construction projects based on the line of balance (LOB) technique and constraint programming. In addition, an LOB‐based scheduling optimization model for resource leveling is proposed. This model retains the advantages of the conventional models, including multiple‐resource management and natural rhythm concept, and showcases new abilities: scheduling optimization without specifying a fixed schedule; scheduling optimization on more comprehensive optimization objects and variable values; maintaining continuity of resource while completely eliminating the occurrence of idle time; handling more comprehensive constraints after the addition of logical constraints and explicit expression of certain new constraints. The flexibility, practicality, and solution quality of the proposed model were enhanced accordingly. Further, a scheduling system was developed to assist in schedule optimization and visualization. Lastly, effectiveness of the proposed model was verified based on four case studies involving three case projects investigated in extant LOB‐based studies. [ABSTRACT FROM AUTHOR]

The line-of-balance (LOB) technique has demonstrated many advantages in scheduling repetitive projects, one of which is that it allows more than one crew to be hired by an activity concurrently. The deadline satisfaction problem in LOB scheduling (DSPLOB) aims to find an LOB schedule such that the project is completed within a given deadline and the total number of crews is minimized. Previous studies required a strict application of crew work continuity, which may lead to a decline in the competitiveness of solutions. This paper introduces work interruptions into the DSPLOB and presents a biobjective optimization model that can balance the two conflicting objectives of minimizing the total number of crews and maximizing work continuity. An efficient version of the ϵ-constraint method is customized to find all feasible tradeoff solutions. Then, these solutions are further improved by an automated procedure to reduce the number of interruptions for each activity without deteriorating the performance in both the objectives. The effectiveness and practicability of the proposed model are verified using a considerable number of instances. The results show that introducing work interruptions provides more flexibility in reducing the total number of crews under the LOB framework, especially for serial projects with a tight deadline constraint. [ABSTRACT FROM AUTHOR]

The line-of-balance (LOB) technique is considered as an effective tool for planning and scheduling linear repetitive construction projects. One of the main assumptions of the LOB technique is the uniformity and constancy of production rate for an activity. Moreover, some aspects of the LOB technique can be modified in order to suit the nature of construction projects. This paper proposes a hybrid approach for scheduling linear projects that optimizes resource allocation using the LOB scheduling technique. The paper presents an optimization model for resolving resource constraint dilemmas in linear scheduling projects. The proposed model utilizes a Matrix Laboratory (MATLAB) code using graph theory as a searching algorithm to automate the model formulation. The novelty of the model is that it supports decision makers in formulating the optimal crews routing among various activities and also considering the allocation of multitasking skilled crews. A case study for a repetitive 4-km sewage pipeline installation is used to test the capabilities of the proposed model. Results show that the model can feasibly reduce the number of crews employed in linear repetitive construction projects. [ABSTRACT FROM AUTHOR]

The line of balance method that provides continuous and uninterrupted use of resources is one of the best methods for repetitive project resource management. This paper develops a resource leveling algorithm based on the backward controlling activity in line of balance. The backward controlling activity is a kind of special activity, and if its duration is prolonged the project duration could be reduced. It brings two advantages to the resource leveling: both the resource allocated on the backward activity and the project duration are reduced. A resource leveling algorithm is presented which permits the number of crews of the backward controlling activity to be reduced until the terminal situation is reached, where the backward controlling activity does not exist or the number of crews cannot be reduced. That adjustment enables the productivity of all activities to be consistent. An illustrative pipeline project demonstrates the improvement in resource leveling. And this study designed a MATLAB program to execute the design algorithm. The proposed model could help practitioners to achieve the goals of both resource leveling and project duration reduction without increasing any resource. [ABSTRACT FROM AUTHOR]

Scheduling repetitive work by multiple crews is a typical mission for schedulers, who must arrange the productivity, number, and size of crews and their lead or lag. Currently, the Linear Scheduling Method (LSM) and Line-of-Balance (LOB) can analyze repetitive work. These two related methods possess virtues, but lack a unified theory so that they could complement each other. Therefore, this paper explores a new approach. Its contribution to the body of knowledge is threefold: First, dissimilarities in activity representation, start point, and velocity measurement are reviewed and their causes are explained graphically and mathematically. Second, multiple crews are expressed with singularity functions in a three-part model—crew assignment, crew utilization, and crew linear schedule. The model is automatically updated when parameters are modified for “what-if” analyses. Third, LSM and LOB are united so that crews can be optimized seamlessly. This research advances theory on deploying multiple crews on construction projects. [ABSTRACT FROM AUTHOR]

Projects with repeating activities, such as multistory buildings and highways, present unique scheduling challenges. This paper presents the necessary requirements that scheduling systems should address to meet the needs and complexities of repetitive projects in practice. The repetitive scheduling method (RSM) provides a unified scheduling framework that applies to all types of repetitive projects. In RSM, projects are classified as discrete (vertical) or continuous (horizontal or linear) and then as uniform and nonuniform, depending on whether progress is measured using a counting scale or a dominant-attribute scale. RSM modeling elements include three types of activities (line, block, and bar) and 10 types of relationships (links) between activities. RP2, a computer program developed by the authors to validate the proposed scheduling approach, is used to develop the production diagrams and tabular reports of the target schedule for a complex of four-story apartment buildings for a low-income housing project. Sufficient detail is provided so that the project and its target schedule can be used to validate future research and to verify other systems. [ABSTRACT FROM AUTHOR]

The objective of this study is to propose a new method to enhance the time- and cost-planning process for the construction of building foundations via integration of discrete-event simulation, line-of-balance diagram, and Building Information Modeling (BIM) tools. In order to calibrate a discrete-event simulation model, field measurements of workflow, resource consumption, activity duration, and restrictions were obtained from real construction projects. Based on Lean Construction methods and line-ofbalance diagrams, which allow reduction in time and cost, a number of planning alternatives were proposed. In addition, virtual animation of such alternatives was performed through BIM methodologies. It is concluded that planning tool integration is a robust technique for planning and decision-making in civil engineering projects. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Line-of-balance (LOB) methodology produces a work schedule in which resource allocation is automatically performed to provide a continuous and uninterrupted use of resources, but the distribution of resources could be further improved by resource leveling even if multiple resources are involved. The objective of this study is to develop a genetic algorithm (GA)-based multiresource leveling model for schedules that are established by LOB. The proposed model postulates that the production rate and duration of an activity are governed by the resource that requires the longest duration in completing a unit. Once the LOB schedule is established, resource leveling is performed according to the principle of optimum crew size that makes use of a utility data curve, which shows that productivity will suffer if the crew size is different than the optimum crew size, and the principle of natural rhythm that allows shifting the start times of an activity forward or backward at different units of production by changing the number of crews employed. The duration of an activity in any one unit and the precedence relationships between activities do not change during the leveling procedure. When applied to the LOB schedule of a pipeline project that was used to illustrate the model, it was observed that the proposed multiresource leveling model provided a smoother resource utilization histogram while maintaining optimum productivity. [ABSTRACT FROM AUTHOR]

Repetitive projects require schedules that ensure the uninterrupted usage of resources from a unit to similar units in a repetitive activity while maintaining logical dependency constraints. The critical path method (CPM) is the most widely used and accepted planning and scheduling method for traditional (nonrepetitive) projects. However, CPM does not suit the planning and scheduling needs of repetitive projects. Consequently, resource-driven techniques, such as line of balance (LOB), have been used to schedule repetitive projects that ensure work continuity. LOB is primarily a graphical technique that lacks the analytical qualities of CPM scheduling. A need for an analytical technique fulfilling characteristics of repetitive projects has been reported in the literature. Few attempts have been made to combine the benefits of CPM and LOB techniques in planning and scheduling of repetitive projects. In this paper, an integrated CPM and LOB model has been developed to schedule repetitive projects in an easy nongraphical manner, considering both logic dependency and resource continuity constraints. Overlapping activities of a single typical unit are used to model duration and logical relationships of repetitive activities. The proposed model essentially consists of four steps. In the first step, basic LOB calculations are performed to ensure resource continuity. Activity duration along all repetitive units is calculated in the second step. In the third step, overlapping activities are used to model logical relationships between consecutive activities. Next, CPM time analysis is performed to specify activities' timings and floats and project completion time. An example application is presented to illustrate implementation and features of the proposed model. [ABSTRACT FROM AUTHOR]

Repetitive projects require schedules that ensure the uninterrupted usage of resources from a unit to similar units in a repetitive activity while maintaining logical dependency constraints. The critical path method (CPM) is the most widely used and accepted planning and scheduling method for traditional (nonrepetitive) projects. However, CPM does not suit the planning and scheduling needs of repetitive projects. Consequently, resource-driven techniques, such as line of balance (LOB), have been used to schedule repetitive projects that ensure work continuity. LOB is primarily a graphical technique that lacks the analytical qualities of CPM scheduling. A need for an analytical technique fulfilling characteristics of repetitive projects has been reported in the literature. Few attempts have been made to combine the benefits of CPM and LOB techniques in planning and scheduling of repetitive projects. In this paper, an integrated CPM and LOB model has been developed to schedule repetitive projects in an easy nongraphical manner, considering both logic dependency and resource continuity constraints. Overlapping activities of a single typical unit are used to model duration and logical relationships of repetitive activities. The proposed model essentially consists of four steps. In the first step, basic LOB calculations are performed to ensure resource continuity. Activity duration along all repetitive units is calculated in the second step. In the third step, overlapping activities are used to model logical relationships between consecutive activities. Next, CPM time analysis is performed to specify activities' timings and floats and project completion time. An example application is presented to illustrate implementation and features of the proposed model. [ABSTRACT FROM AUTHOR]

Abstract: A number of linear and integer programming techniques have been used to minimize the total cost of earthwork by considering the various factors involved in the process. Although these models often ensure a global optimum for the problem, they required sophisticated formulations and are quite involved in their setup and definition as well as being expensive computationally and therefore may be of limited use in real life. In construction practice, Mass-haul diagrams (MD) have been an essential tool for planning earthwork construction for many applications including roadwork, piping, and other linear infrastructure facilities. One of the most common heuristics that is used widely by practicing engineers in the field to balance the MD is the “shortest-haul-first” strategy. Balancing the MD using this heuristic is usually carried out either graphically on the drawing, or manually by computing values from the mass-haul diagram itself. However performing this approach graphically or manually is fairly tedious and time consuming. In addition manual and graphical approaches are prone to error. More importantly, if the project considered has a large number of stations (in the order of hundreds), then performing this balance manually becomes impractical. A robust algorithm is therefore needed that can automatically balance the MD. The research discussed here presents a formal definition of an algorithm that uses a sequential pruning technique for automatically computing balances of mass-haul diagrams. It is shown that the new algorithm is more efficient than existing integer programming techniques and computationally runs in level of complexity of O(log n) time in most cases. Thus this algorithm can handle problems with a large number of stations within a reasonable amount of time. In addition, a computer implementation and extensive computational experiments are provided. Suggestions for how this algorithm can be used in cost-based or grade-based optimization of hauling distances and quantities are discussed. [Copyright &y& Elsevier]

In this paper, we study several interesting optimal-ratio region detection (ORD) problems in d-D (d ≥ 3) discrete geometric spaces, which arise in high dimensional medical image segmentation. Given a d-D voxel grid of n cells, two classes of geometric regions that are enclosed by a single or two coupled smooth heighfield surfaces defined on the entire grid domain are considered. The objective functions are normalized by a function of the desired regions, which avoids a bias to produce an overly large or small region resulting from data noise. The normalization functions that we employ are used in real medical image segmentation. To our best knowledge, no previous results on these problems in high dimensions are known. We develop a unified algorithmic framework based on a careful characterization of the intrinsic geometric structures and a nontrivial graph transformation scheme, yielding efficient polynomial time algorithms for solving these ORD problems. Our main ideas include the following. We observe that the optimal solution to the ORD problems can be obtained via the construction of a convex hull for a set of O(n) unknown 2-D points using the hand probing technique. The probing oracles are implemented by computing a minimum s-t cut in a weighted directed graph. The ORD problems are then solved by O(n) calls to the minimum s-t cut algorithm. For the class of regions bounded by a single heighfield surface, our further investigation shows that the O(n) calls to the minimum s-t cut algorithm are on a monotone parametric flow network, which enables to detect the optimal-ratio region in the complexity of computing a single maximum flow. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Considering the learning effect while planning and scheduling repetitive construction projects can help provide a realistic forecast of their duration and resource requirements. This paper has developed an improved learning curve (LC) to replace the log-linear LC for monitoring improvement in workers' performance. The improved LC assumes that the manual work time of the specific unit converges to a nonzero constant rather than zero under a large number of repetitions. It also takes into account the influence of workers' prior experience and machinery in the learning process. An improved line-of-balance (LOB) model is then presented by integrating the proposed LC and a mechanism of resource allocation. The proposed LOB model can make use of the learning effect to minimize the total resource usage of a project, while meeting the requirements for work continuity and the target deadline of each activity. An illustrative example has been cited to demonstrate the capability of the model. The technique can help planners use the learning effect to get a more realistic and optimal schedule about resource utilization. [ABSTRACT FROM AUTHOR]