Production rates for various activities and overall construction project duration are significantly influenced by crew formation. Crews are composed of available renewable resources. Construction companies tend to reduce the number of permanent employees, which reduces fixed costs, but at the same time limits production capacity. Therefore, construction project planning must be carried out by means of scheduling methods which allow for resource constrains. Authors create a mathematical model for optimized scheduling of linear construction projects with consideration of resources and work continuity constraints. Proposed approach enables user to select optimal crew formation under limited resource supply. This minimizes project duration and improves renewable resource utilization in construction linear projects. This paper presents mixed integer linear programming to model this problem and uses a case study to illustrate it.

The article presents the problem of scheduling a multi-stage project with limited availability

of resources with the discounted cash flow maximization criterion from the perspective of

a contractor. The contractor’s cash outflows are associated with the execution of activities.

The client’s payments (cash inflows for the contractor) are performed after completing the

agreed project’s stages. The proposed solution for this problem is the use of insertion algorithms.

Schedules are generated using forward and backward schedule generation schemes

and modified justification techniques. The effectiveness of the proposed procedures is the

subject of the examination with the use of standard test instances with additionally defined

financial settlements of a project.

A project scheduling problem investigates a set of activities that have to be scheduled

due to precedence priority and resource constraints in order to optimize project-related

objective functions. This paper focuses on the multi-mode project scheduling problem concerning

resource constraints (MRCPSP). Resource allocation and leveling, renewable and

non-renewable resources, and time-cost trade-off are some essential characteristics which are

considered in the proposed multi-objective scheduling problem. In this paper, a novel hybrid

algorithm is proposed based on non-dominated sorting ant colony optimization and genetic

algorithm (NSACO-GA). It uses the genetic algorithm as a local search strategy in order to

improve the efficiency of the ant colony algorithm. The test problems are generated based on

the project scheduling problem library (PSPLIB) to compare the efficiency of the proposed

algorithm with the non-dominated sorting genetic algorithm (NSGA-II). The numerical result

verifies the efficiency of the proposed hybrid algorithm in comparison to the NSGA-II

algorithm.

Redundancy based methods are proactive scheduling methods for solving the Project

Scheduling Problem (PSP) with non-deterministic activities duration. The fundamental

strategy of these methods is to estimate the activities duration by adding extra time to the

original duration. The extra time allows to consider the risks that may affect the activities

durations and to reduce the number of adjustments to the baseline generated for the project.

In this article, four methods based on redundancies were proposed and compared from two

robustness indicators. These indicators were calculated after running a simulation process.

On the other hand, linear programming was applied as the solution technique to generate

the baselines of 480 projects analyzed. Finally, the results obtained allowed to identify the

most adequate method to solve the PSP with probabilistic activity duration and generate

robust baselines.

Most construction projects involve subcontracting some work packages. A subcontractor is employed on the basis of their bid as well as according to their availability. A viable schedule must account for resource availability constraints. These resources (e.g. crews, subcontractors) engage in many projects, so they become at the disposal for a new project only in certain periods. One of the key tasks of a planner is thus synchronizing the work of resources between concurrent projects. The paper presents a mathematical model of the problem of selecting subcontractors or general contractor’s crews for a time-constrained project that accounts for the availability of contractors, as well as for the cost of subcontracting works. The proposed mixed integer-binary linear programming model enables the user to perform the time/cost trade-off analysis.

Most scheduling methods used in the construction industry to plan repetitive projects assume that process durations are deterministic. This assumption is acceptable if actions are taken to reduce the impact of random phenomena or if the impact is low. However, construction projects at large are notorious for their susceptibility to the naturally volatile conditions of their implementation. It is unwise to ignore this fact while preparing construction schedules. Repetitive scheduling methods developed so far do respond to many constructionspecific needs, e.g. of smooth resource flow (continuity of work of construction crews) and the continuity of works. The main focus of schedule optimization is minimizing the total time to complete. This means reducing idle time, but idle time may serve as a buffer in case of disruptions. Disruptions just happen and make optimized schedules expire. As process durations are random, the project may be delayed and the crews’ workflow may be severely affected to the detriment of the project budget and profits. For this reason, the authors put forward a novel approach to scheduling repetitive processes. It aims to reduce the probability of missing the deadline and, at the same time, to reduce resource idle time. Discrete simulation is applied to evaluate feasible solutions (sequence of units) in terms of schedule robustness.

The construction contractor is concerned with reducing the cost of the project, including reducing unnecessary downtime. This is achieved when resources are fully utilized; this means the crews work continuously moving without interruption from one location to the other. However, any disturbance in the optimally scheduled workflow caused by random events is likely to result in delays, interruptions in the crews work, and productivity losses. There is therefore a need for scheduling methods that allow plans to be more resilient to disruptions and ensure a reduction in downtime and implementation costs. The authors put forward a proactive-reactive approach to the schedule risk management. Proposed method makes it possible to protect schedule deadlines from the impact of risk factors by allocating time buffers (proactive approach). It also takes into account the measures that managers take during execution in response to delays that occur, such as changing construction methods, employing extra resources, or working overtime (reactive approach). It combines both ideas and is based on project simulation technique. The merits of the proposed approach are illustrated by a case of a repetitive project to erect a number of buildings. The presented example proves that the proposed method enables the planner to estimate the scale of delays of processes’ start and consider the impact of measures to reduce duration of processes in particular locations taken in reaction to delays. Thus, it is possible to determine the optimal schedule, at which the costs of losses associated with delays and downtime are minimal.

It is a usual practice for a contractor to deliver several projects at a time. Typically, the projects involve similar types of works and share the same pool of resources (i.e. construction crews). For this reason, the company’s portfolio of orders considered for a particular planning horizon can be modeled as a project with repeatable processes to be performed in heterogeneous units located in a number of construction sites. Its scheduling requires determining the best sequence of the resources’ moving from unit to unit while minding the due dates related with particular orders as well as resource continuity constraints. The authors present a model of this scheduling problem in the form of a mixed-integer linear program. The aim is to schedule a portfolio of projects in a way that minimizes the total of the resource idle time-related costs, the indirect costs, and the delay penalties. The model can be solved by means of a general-purpose solver. The model is applied to schedule a portfolio of multifamily housing projects.

Duration of construction projects can be reduced by harmonizing construction processes: adjusting productivity rates of specialized crews and enabling the crews to work in parallel as in a production line. This is achievable in the case of projects whose scope can be divided into units where a similar type of work needs to be conducted in the same sequence. A number of repetitive project scheduling methods have been developed to assist the planner in minimizing the execution time and smoothing resource profiles. However, the workflow, especially in construction, is subject to disturbance, and the actual process durations are likely to vary from the as-scheduled ones. The inherent variability of process durations results not only in delays of a particular process in a particular unit but also in the propagation of disruptions throughout the initially well-harmonized schedule. To counteract the negative effects of process duration variability, a number of proactive scheduling methods have been developed. They consist in some form of predicting the conditions to occur in the course of the project and implementing a strategy to mitigate disturbance propagation. This paper puts forward a method of scheduling repetitive heterogeneous processes. The method aims to reduce idle time of crews. It is based on allocating time buffers in the form of breaks between processes conducted within units. The merits of the method are illustrated by an example and assessed in the course of a simulation experiment.