Mirko Pšunder

Automated construction activity monitoring system

Building activities are inadequately monitored during construction projects when attempting to satisfy the need for information, especially in those cases of unforeseen events and conditions on-site. Many IT-supported methods have been introduced, but so far none has been able to deliver satisfactory and reliable information. This paper presents a combined method, consisting of three components: an automated activity tracking subsystem based on image recognition, an automated material tracking subsystem, and a mobile computing supported communication environment. All subsystems are based on the same 4D model of a building.

MINLP optimization model for the nonlinear discrete time-cost trade-off problem

This paper presents the mixed-integer nonlinear programming (MINLP) optimization model for the nonlinear discrete time-cost trade-off problem (NDTCTP). The nonlinear total project cost objective function of the proposed MINLP optimization model is subjected to a rigorous system of generalized precedence relationship constraints between project activities, project duration constraints, logical constraints, and a budget constraint. By means of the proposed MINLP optimization model, one can obtain the minimum total project cost, the project schedule with the optimal discrete start times and the optimal discrete durations of the activities, as well as the optimal time-cost curves of the project. The proposed model yields the exact optimum solution of the NDTCTP. Solving the NDTCTP, using the proposed MINLP model, avoids the need for (piece-wise) linear approximation of the nonlinear expressions. The MINLP model handles the discrete variables explicitly and requires no rounding of the continuous solution into an integer solution. The applicability of the proposed optimization model is not limited to weakly NDTCTPs. A numerical example from the literature and an example of the project time-cost trade-off analysis are presented at the end of the paper in order to show the advantages of the proposed model.

COST OPTIMIZATION OF TIME SCHEDULES FOR PROJECT MANAGEMENT

Abstract The paper presents the cost optimization of the time schedules for project management. The nonlinear programming (NLP) model for the cost optimization of the time schedules under the generalized precedence relations between the project activities was developed and applied. The existing NLP optimization models have focused on the cost optimal solution of the project scheduling problems which include simplifying assumptions regarding the precedence relationships among the project activities. In this way, this research work aims to propose the NLP optimization model for making optimal time-cost decisions applicable to actual projects in project management. The generalized reduced-gradient method was used for the NLP optimization. The obtained results include the minimum total cost project schedules and the optimal project time-cost curves. The proposed optimization approach enables the insight into the interdependence between the project duration and the total project cost. The decision-maker can more effectively estimate the effect of the project deadline on a total project cost before the submission of a tender. An application example and an example of the time-cost trade-off analysis are presented in the paper to demonstrate the advantages of the proposed approach.

Cost Optimal Project Scheduling

Cost Optimal Project Scheduling This paper presents the cost optimal project scheduling. The optimization was performed by the nonlinear programming approach, NLP. The nonlinear total project cost objective function is subjected to the rigorous system of the activity precedence relationship constraints, the activity duration constraints and the project duration constraints. The set of activity precedence relationship constraints was defined to comprise Finish-to-Start, Start-to-Start, Start-to-Finish and Finish-to-Finish precedence relationships between activities. The activity duration constraints determine relationships between minimum, maximum and possible duration of the project activities. The project duration constraints define the maximum feasible project duration. A numerical example is presented at the end of the paper in order to present the applicability of the proposed approach.