The paper presents the problem of optimal management of the resources in multiunit construction project. During the creation of the models of this kind of the project the flow-shop system is rarely used. Flow-shop system now is widely applied in modelling of industrial processes, computer systems. In the model presented in the paper flow shop system with teams of working groups is used. It allows its users to shorten the time of realization of multiunit construction projects in a significant way, because works in the project can be realized by teams of working groups of any cardinality. This is new model of multiunit construction project which has not been examined in field of scheduling of construction project yet. The presented optimization model of multiunit construction project with teams of working groups performing one type of work is NP-hard optimization problem. During the scheduling of such projects there was an artificial intelligence tool used, i.e. metaheuristic tabu search algorithm. Tabu search algorithm can provide solutions of very good quality. The paper also presents a calculation example of the above mentioned problem. The obtained in calculation example result is fully satisfactory.

The article presents the profit optimization model for multi-unit construction projects. Such projects constitute a special case of repetitive projects and are common in residential, commercial, and industrial construction projects. Due to the specific character of construction works, schedules of such projects should take into account many different aspects, including durations and costs of construction works, the possibility of selecting alternative execution modes, and specific restrictions (e.g., deadlines for the completion of units imposed by the investor). To solve the NP-hard problem of choosing the order of units’ construction and the best variants of works, the authors used metaheuristic algorithms (simulated annealing and genetic search). The objective function in the presented optimization model was the total profit of the contractor determined on the basis of the mathematical programming model. This model takes into account monthly cash flows subject to direct and indirect costs, penalties for missing deadlines, costs of work group discontinuities, and borrowing losses. The presented problem is very important for maintaining a good financial condition of the enterprise carrying out construction projects. In the article, an experimental analysis of the proposed method of solving the optimization task was carried out in a model that showed high efficiency in obtaining suboptimal solutions. In addition, the operation of the proposed model has been presented on a calculation example. The results obtained in it are fully satisfying.

The article presents the cost optimization model for multiunit construction projects. Multiunit projects constitute a special case of repetitive projects. They consist in the realization of many different, when it comes to size, types of residential, commercial, industrial buildings or engineering structures. Due to the specific character of construction works, actual schedules of such projects should not only take into account real costs of construction, but also be subject to specific restrictions, e.g. deadlines for the completion of units imposed by the investor. To solve the NP-hard problem of choosing the order of units’ construction there was metaheuristic algorithm of simulated annealing used. The objective function in the presented optimization model was the total value of the project cost determined on the basis of the mathematical programming model, taking into account direct and indirect costs, costs of missing deadlines and costs of work group discontinuities. In the article, an experimental analysis of the proposed method of solving the optimization task was carried out in a model that showed high efficiency in obtaining suboptimal solutions. In addition, the operation of the proposed model has been presented on a calculation example. The results obtained in it are fully satisfying.

Planning problems are particularly important for the production processes of precast reinforced concrete elements. Currently used modeling of these processes is based on the flow shop problem. Flow shop models are usually used in Enterprise Resource Planning systems, which, however, may not take into account the specifics of the production of such elements. The article presents a new model for scheduling the production of reinforced concrete prefabricated elements, which is distinguished by the possibility of carrying out activities by more than one working group. An additional new constraint is the possibility of parallel performance of some works, which may occur during their production. Also, there will be an individual order of elements assumed for each of the activities. New objective functions will be considered – the sum of idle times of working groups and the total type changes of precast components. The presented scheduling model contains an NP-hard discrete optimization problem. For this reason, metaheuristics were used in the article to solve optimization problems: the simulated annealing algorithm and the tabu search algorithm. Verification of the results obtained with the use of these algorithms confirmed their high efficiency. The application of the presented scheduling model illustrates a practical case study showing the effectiveness of the used algorithms.

Construction projects are often delayed. Their budgets are being exceeded. This is partly because construction project models rarely take human factors into account. The article focuses on the repetitive multi-unit projects that are often found in construction practices. They are an excellent example of construction works for which the optimization of certain processes can bring measurable financial benefits. In particular, the focus was on improving the key investment success indicator, the total cost of a project. This article presents the use of learning and forgetting phenomenon to improve construction schedules. The authors proposed an innovative model of the construction phase and optimized the schedule using a proprietary calculation algorithm using the simulated annealing phenomenon. The method was verified by a series of experiments and showcased by a case study. The results show that the presented methods can improve the construction planning process and better reflect the current construction conditions. The findings may impact residential, infrastructure, industrial, and commercial construction branches.

The problem of optimal scheduling of construction production is particularly important in the case of production processes of concrete precast structural elements. The most important features characterizing this type of construction production are as follows: - the necessity to produce precast elements in factory conditions in order to make the production process independent of the weather conditions, - the repeatability of production processes of precast elements. The paper presents a model for scheduling of the production process of concrete precast structural elements. The model is based on the hybrid flow shop problem (HFS problem), in which it is possible to include more than one device/equipment or group of workers performing one type of production process. The model respects the constraints that are characteristic of the production processes of such elements. The issue of discrete optimization, presented in the paper, is NP-hard. Therefore, the authors proposed the original solution of an optimization task in the model using the simulated annealing metaheuristic algorithm. The application of the presented scheduling model is illustrated by a practical calculation example showing the effectiveness of the used optimization algorithm. The model can be successfully used to solve planning tasks of the production process in plants producing concrete precast elements in order to significantly shorten the duration of production process.