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Project scheduling/rescheduling occurs in all stages of projects, from feasibility stage to monitoring stage to completion. Since the late 1950s, network‐based techniques CPM (critical path method) and PERT (programme evaluation review technique) are the techniques commonly used for project management. However, there are limitations in working with these tools that need to be overcome. Also, the computing ef. ciency of classic CPM/PERT analysis needs to be enhanced. Substantial research has been carried out globally in this field covering all areas of project scheduling: time scheduling, resource scheduling, cost scheduling, modern project management techniques, advanced mathematical models used for construction scheduling, and so on. To understand and document this research status, the authors have carried out an extensive study of various journals, published and unpublished research papers, and present this literature review.

The implementation and control processes of project planning and scheduling involve a wide range of methods and tools. Despite the development and modification and integration of the project management theory with newer scheduling approaches in particular, practitioners’ views on the efficiency and effectiveness of these methods and tools differ. This situation can be attributed in part to a lack of understanding of the most appropriate basis for implementing these methods and tools. This study, therefore, aims to overcome this deficiency by conceptualizing and adopting a taxonomy of planning and scheduling methods.

The study is based on a review and discourse analysis of the literature covering a large number of theoretical and empirical studies. The underlying theories of various planning and scheduling methods were analyzed with respect to the taxonomy criteria adopted in the study.

Using the taxonomy, the key characteristics of planning and scheduling methods considered in this study were identified and interpreted. These included concepts and theories; key features; suitability and usability; and benefits and limitations. Overall, the findings suggest that project managers should consider taxonomy as a support tool for selecting and prioritizing the most appropriate method or combination of methods for managing their projects. Recommendations include the need for more advanced or multi-dimensional taxonomies to cope with the diversity of project type and size.

The results of the study allow project managers to improve their current practices by utilizing taxonomy when considering the implementation of planning and scheduling methods. Moreover, taxonomy can be considered as a tool to promote learning on the part of those less experienced in planning and scheduling. Taxonomy can be considered as an initial platform for further research in this area.

Historically, scheduling of production activities has been one of the most important management problems. Scheduling involves the planning and the co‐ordination of the various activities to achieve the optimum utilisation of resources over a given time period. Production scheduling differs with the typology of the production systems. Various production systems that are encountered in practice are: continuous production, mass production, batch production, job shop production and projects. In this article, we attempt only to discuss the project scheduling problems.

The purpose of this paper is to present a new method for project tracking and control of integrated offsite and onsite activities in modular construction considering practical characteristics associated with this type of construction.

The design embraces building information modelling and integrates last planner system (LPS), linear scheduling method (LSM) and critical chain project management (CCPM) to develop tracking and control procedures for modular construction projects. The developed method accounts for constraints of resources continuity and uncertainties associated with activity duration. Features of proposed method are illustrated in a case example for tracking and control of modular projects.

Comparison between developed schedule and Monte Carlo simulation showed that baseline duration generated from simulation exceeds that produced by developed method by 12% and 10% for schedules with 50% and 90% confidence level, respectively. These percentages decrease based on interventions of members of project team in the LPS sessions. The case example results indicate that project is delayed 5% and experienced cost overrun of 2.5%.

Developed method integrated LPS, LSM and CCPM while using metrics for reliability assessment of linear schedules, namely, critical percent plan complete (PPC_cr) and buffer index (BI). PPC_cr and BI measure percentage of plan completion for critical activities and buffer consumption, respectively. The developed method provides a systematic procedure for forecasting look-ahead schedules using forecasting correction factor Δ_t and a newly developed tracking and control procedure that uses PPC_cr and BI. Quantitative cost analysis is also provided to forecast and monitor project costs to prove the robustness of proposed framework.

The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).

The model contains a cost objective function, generalized precedence relationship constraints, activity duration and start time constraints, lag/lead time constraints, execution mode (EM) constraints, project duration constraints, working time unit assignment constraints and resource constraints. The mixed-integer nonlinear programming (MINLP) superstructure of discrete solutions covers time–cost–resource options related to various EMs for project activities as well as variants for production process implementation.

The proposed model provides the exact optimal output data for project management, such as network diagrams, Gantt charts, histograms and S-curves. In contrast to classic scheduling approaches, here the optimal project structure is obtained as a model-endogenous decision. The project planner is thus enabled to achieve optimization of the production process simultaneously with resource-constrained scheduling of activities in discrete time units and at a minimum total cost.

A set of application examples are addressed on an actual construction project to display the advantages of proposed model.

The unique value this paper contributes to the body of knowledge reflects through the proposed MINLP model, which is capable of performing the exact cost optimization of production process (where presence and number of activities including their mutual relations are dealt as feasible alternatives, meaning not as fixed parameters) simultaneously with the associated resource-constrained project scheduling, whereby that is achieved within a uniform procedure.

Basic project control through traditional methods is not sufficient to manage the majority of real-time events in most construction projects. The purpose of this paper is to propose a Dynamic Scheduling (DS) model that utilizes multi-objective optimization of cost, time, resources and cash flow, throughout project construction.

Upon reviewing the topic of DS, a worldwide internet survey with 364 respondents was conducted to define end-user requirements. The model was formulated and solution algorithms discussed. Verification was reported using predefined problem sets and a real-life case. Validation was performed via feedback from industry experts.

The need for multi-objective dynamic software optimization of construction schedules and the ability to choose among a set of optimal alternatives were highlighted. Model verification through well-known test cases and a real-life project case study showed that the model successfully achieved the required dynamic functionality whether under the small solved example or under the complex case study. The model was validated for practicality, optimization of various DS schedule quality gates, ease of use and software integration with contemporary project management practices.

Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste.

Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste.

The paper illustrates the importance of DS in construction, identifies the user needs and overviews the development, verification and validation of a model that supports the generation of high-quality schedules beneficial to large-scale projects.

The article aims to critically analyze the project management developed by research laboratories of a Brazilian university in order to enhance their performance. For this, a critical analysis was performed to identify existing opportunities about the management of schedules and resources. Additionally, a software was developed to enable performance improvement.

The methodological procedures used were literature review, for a theoretical foundation, and case study conducted with semi-structured interviews, documentary research and on-site visits. Through a detailed critical analysis of the laboratories' management, it was possible to understand the activities developed and map the main difficulties observed.

A total of five plausible points of improvement were identified, namely reduced teams and accumulation of activities; team seasonality; centralized management; deviations from projects and schedule control. Based on the theoretical foundation, it has been proposed adjustments to minimize the mentioned difficulties that can greatly contribute for better management efficiency of multiple research projects. In addition, a software was structured based on the proposed improvements. The laboratories' performance was monitored for a month and significant improvements were observed.

The information presented here may be of great value to other researchers interested in enhancing research laboratory performance.

The academic literature presents several examples of project management guidelines application in different organizations; however, there are few studies about the application of them in research laboratories and how to improve their performance.

A survey of project scheduling problems since 1973 limited to work done specifically in the project scheduling area (although several techniques developed for assembly line balancing and job‐shop scheduling can be applicable to project scheduling): the survey includes the work done on fundamental problems such as the resource‐constrained project scheduling problem (RCPSP); time/cost trade‐off problem (TCTP); and payment scheduling problem (PSP). Also discusses some recent research that integrates RCPSP with either TCTP or PSP, and PSP with TCTP. In spite of their practical relevance, very little work has been done on these combined problems to date. The future of the project scheduling literature appears to be developing in the direction of combining the fundamental problems and developing efficient exact and heuristic methods for the resulting problems.

The overall contribution of this work is to provide a usable maturity model for collaborative scheduling (CS) that extends the literature, identifies inconsistencies in schedule development, and improves collaboration in the construction industry.

Via subject matter expert elicitation and focus groups, the maturity model establishes five pillars of collaboration—scheduling significance, planners and schedulers, scheduling representation, goal alignment with owner, and communication. The maturity model is then validated through iterative feedback and chi-squared statistical analysis of data obtained from a survey. The five pillars are tied to the literature and previous work in CS.

The analysis shows that current industry projects are not consistent in collaboration practice implementation, and the maturity model identifies areas for collaboration improvement. The study's contributions to the body of knowledge are (1) developing a maturity model-based approach to define and measure the current level of collaboration and (2) discovering the level of consistency in scheduling collaboration practice implementation.

The findings provide a benchmark for self-evaluation and peer-to-peer comparison for project managers. The model is also useful for project managers to develop effective strategies for improvement on targeted dimensions and metrics.

The construction engineering and management (CEM) literature does not contain targeted models for scheduling collaboration in the context of maturity and, broadly speaking, neither does the literature at large. The literature also lacks actionable items as presented for the maturity model for collaborative scheduling (MMCS).

The purpose of this paper is to propose a Non-Linear Integer Programming (NLIP) model that solves the resource leveling problem while reducing the negative effect of the total float loss on risk.

An NLIP model is formulated to solve the resource leveling optimization problem incorporating float loss cost (FLC). The proposed model is implemented using “What’s Best solver” for Excel. The FLC is calculated using the float commodity approach. An example is solved using the proposed model in order to illustrate its applicability. Sensitivity analysis is also performed.

The results confirmed that resource leveling reduces the available float of non-critical activities; decreases schedule flexibility and reduces the probability of project completion. The probability of timely completion dropped from 50 percent (for the normal schedule with 32 resource fluctuations) to 13.5 percent for leveled resources with zero fluctuations. Using the proposed method, the number of resource fluctuations is 8 but the probability of completing the project on time improved to 20 percent.

The proposed model allows project managers to exercise new trade-offs between resource leveling and schedule flexibility which will ultimately improve the chances of successful project delivery.

Resource leveling techniques result in reducing the available total float for the non-critical activities. Existing methods focus on moving noncritical activities within their available float and ignore the impact of the resulting float loss. This reduces the schedule flexibility and increase the risk of project delays. The proposed model incorporates the FLC into the resource leveling optimization problem resulting in more efficient schedules with improved resource utilization while keeping some schedule flexibility.