Abstract
This paper presents the integration of mixed-integer nonlinear program (MINLP) and project management tool (PMT) to support sustainable cost-optimal construction scheduling. An integrated structure of a high-level system for exact optimization and PMT was created. To ensure data compatibility between the optimization system and PMT and to automate the process of obtaining a cost-optimal schedule, a data transformation tool (DTT) was developed within a spreadsheet application. The suggested system can determine: (i) an optimal project schedule with associated network diagram and Gantt chart in continuous or discrete time units; (ii) optimal critical and non-critical activities, including their early start, late start, early finish, late finish along with total and free slack times; and (iii) minimum total project cost along with the allocation of direct and indirect costs. The system provides functionalities such as: (i) MINLP can be updated, and schedules can be re-optimized; (ii) the optimal schedule can be saved as a baseline to track changes; (iii) different optimization algorithms can be engaged whereby switching between them does not require model changes; (iv) PMT can be used to track task completion in the optimized schedule; (v) calendar settings can be changed; and (vi) visual reports can be generated to support efficient project management. Results of cost-optimal project scheduling are given in a conventional PMT environment, which raises the possibility that the proposed system will be more widely used in practice. Integration of MINLP and PMT allows each software to be used for what it was initially designed. Their combination leads to additional information and features of optimized construction schedules that would be significantly more difficult to achieve if used separately. Application examples are given in the paper to show the advantages of the proposed approach.
Highlights
In a dynamic environment such as the construction industry, the success of a project is highly dependent on a project manager’s ability to create an optimal schedule for construction activities
Minimum total costs obtained by relaxed mixed-integer nonlinear program (MINLP) optimization shown as visual report of MS Project in form of histogram and S-curve
Minimum totaltotal costs obtained by relaxed MINLP optimization shown as visual report of MS Project in form of histogram and S-curve
Summary
In a dynamic environment such as the construction industry, the success of a project is highly dependent on a project manager’s ability to create an optimal schedule for construction activities. Construction projects commonly require various participants for contracted works and are affected by site specifics as well as weather conditions. Changing site conditions require different procedures and designs that take into account these changing conditions, whether it is a design solution, a change in environmental conditions, or just sustainability factors [2]. A contractor’s ability to prepare a competitive bid for a construction tender still remains crucial for its survival on the market [3]. These particularities, together with the fact that wrong decisions on high-value construction projects can seriously jeopardize a contractor’s business success or even existence in the market, enhancing the need for optimization-supported construction scheduling
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