The present work is an extension of the authors’ previous research, where changes in the dynamic behavior of heat exchangers induced by fouling build-up were studied. In the present work, the authors used the previously elaborated and validated mathematical model of transient heat exchange with the influence of thermal resistance of fouling taken into account. The behavior of specific Heat Exchanger Networks (HENs) coupled with a Crude Distillation Unit together with their control loops is simulated using Simulink/MATLAB and the influence of fouling build-up on specific indices of quality of operation is investigated. According to the presented results, the higher the number of heat exchangers in the PID control loop and the greater the number of heat exchangers interacting in the network, the smaller the influence of fouling on the control quality indices, and in the extreme case, this influence may be negligible. This might be caused by the compensation of the negative effects of fouling build-up when the heat exchangers are interacting in the HEN. Nevertheless, potential adverse effects of fouling on HEN operation can be prevented by periodic adjustments of the optimal values of PID gains.

In this paper, we present the effect of making too many private car journeys on city transport systems. A sustainable approach for the development of transport infrastructure is needed, which takes into account local conditions and needs, especially for areas with a high density of origins and destinations. The criteria for evaluating public transport and bicycle transport are presented, which, if acceptable to city residents, may lead to changes in transportation behaviors and, thus, a more efficient use of transport in daily travels. Factors affecting the mode of transport choice include the duration of particular stages of a journey, such as reaching the location where the first ride commences/driving from the travel origin, waiting for a vehicle (bus journeys) or ride/drive, and reaching the travel destination of the last ride/drive. Additionally, the possibility of using a car and having a seasonal ticket for public transport were taken into account. In this study, the results of detailed travel research in the Polish city of Tarnow were used. It has been proven that the low share of public transport in daily travels is due, among other things, to excessive time to reach a stop and due to walking to journey destinations, whereas the low share of cycling is mainly due to a lack of comfort and safe cycling infrastructure.

Planning the operation of urban public transport vehicles is the first stage of operational planning and consists in combining timetable tips, which are input data, into blocks that constitute the daily tasks of vehicles. For a large mixed fleet of vehicles of various types, especially those with battery power that requires recharging, operating from many depots, with numerous requirements and rolling stock constraints, the problem is a major engineering challenge, even for an experienced team of planners. IT solutions based on realistic, mathematical decision-making models and fast optimization algorithms can be of great assistance. For the problem formulated this way, a mathematical decision model with a multi-criteria objective function was built, taking into account technical, economic, and ecological criteria, natural, and binary decision variables. The model takes into account the real requirements and constraints, a mixed fleet of different types vehicles, including electric buses, multiple depots, technical trips (dead heads), and battery charging. The considered problem is an NP-hard combinatorial optimization problem. The use of classical, exact algorithms to solve this problem is not possible for schedules with many thousands of line trips and fleets of hundreds or thousands of vehicles. This research proposes an original, dedicated heuristic, enabling to obtain an acceptable, but still suboptimal solution, in a very short time. The tests of the proposed heuristic algorithm were carried out on real databases of public transport systems of the two selected medium and large Polish cities. In particular, multiple depots, a mixed fleet of different types of vehicles, and real-world constraints were taken into account. The results of computer experiments carried out using the developed heuristic were compared with the results obtained manually by a team of experienced and expert planners. For the developed multi-criteria decision-making model results comparable to and better than those prepared manually by experts were obtained in a very short time using the proposed heuristics. It is the basis for further development works on expanding the model and improving the optimization algorithm.

Public transport plays an increasingly important role in satisfying the transport needs. Travellers’ requirements regarding the quality of services are increasing. In addition to passenger comfort, other parameters are important...

The optimal vehicle (VSP) and crew (CSP) scheduling problems solving in urban public transportation involves assigning timetabled trips to daily vehicle tasks, called blocks, and next to daily driver tasks, called duties. The aim is to minimize the number of vehicles and drivers. This maximizes usage of the both assets, makes the schedules more convenient for vehicle operations and drivers, and as a result mitigates possible delays, and fits into the legal requirements for the drivers' working time. The scheduling can be done either sequentially or simultaneously. In the former, vehicles are scheduled first, then drivers based on an already constructed vehicle blocks. Whereas in the latter, vehicles and drivers are scheduled at the same time, thus integrated (VCSP). As for the solution methods for the VCSP the Evolutionary Algorithms (EA) play a crucial role in addressing this complex challenge. Moreover, recent publications point out that metaheuristics, in particular the EA, are widely and successfully used in both the sequential and simultaneous solution approaches. The integrated scheduling of vehicles and rivers requires much longer computational time, which often cannot be accepted in practice for the VSP and CSP are usually solved separately by different institutions, i.e., the public transport authority (PTA) and the public transport operator (PTO), respectively. Alternatively, in the sequential approach, that is less computationally demanding, the influence of a solution of the VSP on a solution of the CSP can also be included. To solve sequentially the CSP taking into account an already solved the VSP and its characteristics (e.g., multiple depots, electric vehicles (EVs)), a specific and original EA is proposed in this paper. The algorithm divides vehicle blocks into pieces of work to be assigned to drivers’ duties. The pieces of work can be composed of the entire vehicle blocks as well as their parts, for the algorithm can divide them according to a set of proposed rules. The algorithm was tested on a real-world databases of public transport systems of the three large Polish cities. The results were compared with those obtained manually by a team of experienced transport planners. The crew schedules obtained using the algorithm were comparable or even better than those prepared manually and reached within significantly shorter time.