The actual completion time of construction projects is rarely in accordance with initial plans. This is due to unforeseen events that affect the project execution. In the paper, the authors propose a method of improving the construction schedule reliability. The method is based on the idea of buffers allocation, whose proper sizing helps to reduce negative effects of random conditions on the progress and efficiency of project activities. The authors adopt a proactive approach to the construction of robust schedules to cope with multiple disruptions during project execution, applicable to two processes starting policies (as soon as possible or no sooner than on a predefined date). The proposed method, based on simulation technique and mathematical programming, was illustrated by an example. The results obtained by means of the proposed method were compared, in terms of schedule stability, to those of the float factor heuristic and starting time criticality heuristicprocedures. The method allowed reducing cost of deviations from the planned activity start dates in random conditions. Santrauka Tikrasis statybos projektų baigimo laikas retai atitinka pradinius užsibrėžtus planus. Taip yra dėl nenumatytų atvejų, kurie daro įtaką galutiniam projekto baigimo laikui. Šiame straipsnyje autoriai pristato metodą, kuris pagerina statybos grafikų patikimuma. Jis grindžiamas laiko rezervo paskirstymo idėja, padedančia sumažinti neigiamus atsitiktinių trikdžių poveikius vykdant projektą. Autoriai pritaiko veiksmingą būdą, kuris leidžia išvengti daugelio sutrikimų vykdant projektą. Siūlomas metodas pagrįstas modeliavimu ir matematiniu programavimu, darbe pateiktas jo taikymo pavyzdys. Gauti rezultatai, taikant siūlomą metoda, buvo lyginami įvairiais požiūriais. Metodas leidžia sumažinti išlaidas, kai atsitiktinėmis sąlygomis nukrypstama nuo planuojamų terminų.

A formwork is a structure used to contain poured concrete and to mold it to the required dimensions. Different formwork systems provide a wide range of concrete construction solutions that can be chosen to suit the needs of a particular structure. The selection of panels and the design of the formwork layout for concrete structures, especially if the panels are to be reused many times to form different work zones, are one of the most complex tasks in formwork construction. It influences the quality of work, construction time, site safety and cost. The formwork costs account for a significant part of the total costs for concrete works. The problem of the selection and layout of reusable panel forms is solved mainly based on the intuitive judgment of experienced engineers in collaboration with the form system supplier. This study proposes a mixed integer linear programming modeling approach to support the formwork planning process. The problem consists in determining the number and sizes of the panels according to the geometry of the concrete elements to minimize the rental cost of wall shuttering in a building divided into work zones that are to be completed in sequence, reusing the chosen panels. The model can be solved using typical software dedicated to mixed integer linear programs. A simple example is used to illustrate the efficiency of the proposed approach, where the formwork rental cost is 7.31 % lower than the rental costs of panels and corners optimized without consideration of the reuse in consecutive zones.

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.

Subcontracting has been a worldwide practice in the construction industry. It enables the construction enterprises to focus on their core competences and, at the same time, it makes complex project possible to be delivered. Since general contractors bear full responsibility for the works carried out by their subcontractors, it is their task and their risk to select a right subcontractor for a particular work. Although subcontractor management has been admitted to significantly affect the construction project's performance, current practices and past research deal with subcontractor management and scheduling separately. The proposed model aims to support subcontracting decisions by integrating subcontractor selection with scheduling to enable the general contractor to select the optimal combination of subcontractors and own crews for all work packages of the project. The model allows for the interactions between the subcontractors and their impacts on the overall project performance in terms of cost and, indirectly, time and quality. The model is intended to be used at the general contractor's bid preparation stage. The authors claim that the subcontracting decisions should be taken in a twostage process. The first stage is a prequalification-provision of a short list of capable and reliable subcontractors; this stage is not the focus of the paper. The resulting pool of available resources is divided into two subsets: subcontractors, and general contractor's in-house crews. Once it has been defined, the next stage is to assign them to the work packages that, bound by fixed precedence constraints, form the project's network diagram. Each package is possible to be delivered by the general contractor's crew or some of the potential subcontractors, at a specific time and cost. Particular crews and subcontractors can be contracted more than one package, but not at the same time. Other constraints include the predefined project completion date (the project is not allowed to take longer) and maximum total value of subcontracted work. The problem is modelled as a mixed binary linear program that minimizes project cost. It can be solved using universal solvers (e.g. LINGO, AIMMS, CPLEX, MATLAB and Optimization Toolbox, etc.). However, developing a dedicated decision-support tool would facilitate practical applications. To illustrate the idea of the model, the authors present a numerical example to find the optimal set of resources allocated to a project.