Construction scheduling, in practice, commonly relies on the usage of commercial project management tools (PMT) without specific optimization features. To obtain optimal schedules, planners often need to develop separate optimization models with special tools, which, however, demand further processing and editing of optimization results by PMT into forms expected for project management. In this regard, separation of optimization and PMT also requires considerable additional work for complete and harmonized updating of schedules during construction execution. Mentioned drawbacks and lack of available time may take to deficient construction scheduling during the implementation phase resulting in poor or even insufficient realization of project goals. Therefore, this paper presents an achievements survey on the integration of optimization and PMT that allow sustainable construction scheduling, particularly in terms of continuous optimal time and resource allocation throughout the project life cycle. Such work has not yet been comprehensively done up to now and the present contribution intends to fill a literature gap in the aforesaid area. Following a brief introduction, the optimization platform for construction scheduling is given in the article. Focusing on construction scheduling, an in-depth achievements survey on the integration of heuristics methods, mathematical programming and special solving methods with conventional PMT as well as optimization-based building information modeling (BIM) tools is then performed and findings are reported. The paper ends with conclusions and recommendations for further research.

This paper presents an active building information modeling (BIM) approach for work facilities and the optimal positioning of tower cranes on construction sites with repetitive operations. In this context, the metamorphosis of a passive BIM approach into an active approach is described. Here, the enhancement of the construction-ready BIM model starts with the export of the optimization input parameters, such as the 3D coordinates of the building, perimeter of the construction site, space for feasible solutions, relevant segment of the building with repetitive works, etc. Depending on the complexity of the problem, the user selects a suitable optimization approach and formulates the tower crane positioning optimization problem with the objective of minimizing the total duration of the operation’s cycle. Similarly, according to the model formulation, the user also chooses the optimization tool, including the search algorithm. The final step involves the post-optimal analysis and importing of the optimal solution into the BIM. An application example is demonstrated at the end of the paper to show the advantages of the proposed approach in which the optimization model has significantly improved the initial solution of the crane and depot positions.

Purpose: The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).Design/methodology/approach: 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.Findings: 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.Practical implications: A set of application examples are addressed on an actual construction project to display the advantages of proposed model.Originality/value: 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.