An accurate forecasting system has manifested its role as an enabler in supply chains (SC), which makes the operation possible in a maximally synchronized manner. Its applications have gained the attention of scholars across various disciplines such as forecasting in market behavior analysis and tourism industry; material requirement planning in production; transport and logistics foresight in networks and facilities. Seaports, as specific SC members, are not an exception. Accurate forecasting is needed in almost all aspects of the ports' operation to avoid financial losses related to inappropriate investments and planning. The paper addresses the forecasting of joint demand-supply cargo throughputs in the Adriatic Seaport Koper. The research presents a new forecasting approach, namely, DFA-ARIMAX (Dynamic Factor Analysis-ARIMAX modeling). External economic indicators were screened to obtain useful information using the DFA prior to directing the dynamic factors into the ARIMAX forecasting model. The principal component regression and Monte Carlo framework were included to identify indicators that are unique to the port. Findings revealed that a forecasting system by its enriched capabilities to predict the observed throughputs could be seen as Functional Decision Support System. The benchmarking shows that proposed models outperform competitive models. Practical implications are discussed in detail.

Sustainable engineering is very important for logistics systems. Nowadays, sustainable warehouse management is a key factor in market success. Workforce fluctuation and inverting the number of customers’ demands make a lot of problems in distribution warehouses. This study addresses a sustainable approach for the workforce scheduling problem recognized in a real distribution warehouse. The problem arises from the high variability of demand for workers over one workday, which causes workforce surplus in some periods of the workday and shortages in others. Engineering managers of the distribution warehouse already use different full-time and part-time shifts, and schedule workers on different activities, but they still have significant workforce surpluses or shortages in some periods. This study proposes the scheduling of activities’ execution together with workers to face that variability and decrease the cost of the workforce. This idea comes from the fact that some activities in a distribution warehouse can be done in a specific time period after the need for them occurs. In this way, the variability of demand for workers can be decreased, and a lower workforce cost may be ensured. Based on this idea, the entire problem is modeled as integer linear programming. The real example of the problem is solved, and the proposed model is tested on randomly generated instances of the problem in Python by means of the PuLP linear programming package. The results indicate different positive effects in the manner of sustainable warehouse management: lower workforce costs, time savings, better utilization of all types of resources and equipment, increased employee satisfaction, and so on. For even 61% of instances of the introduced problem, the obtained cost of the workforce is lower by more than 20% if activities’ executions are scheduled together with employees.

Improvements in battery technology make electric vehicles more and more suitable for the use as electricity storages. Many benefits could be achieved by using electric vehicles for storing electricity in their batteries. This paper talks about the idea of electric vehicles as electricity storages in electric power systems. The idea has a great number of supporters, but also a significant part of the professional community believes that is unfeasible. This paper is not classified in either side and strives to give a realistic picture of this idea. For this purpose, findings from papers published in scientific journals are mainly used. There is also some information from websites, mainly for some technical issues. Partly, the opinions of the authors are present. Specificities of EVs and EPSs that enabled the birth of this idea are explained along with proposed concepts through which the idea can be implemented. Keeping with the vehicle to grid concept, issues about the implementation of the idea are considered. Achievements in the practical realization of the idea are also presented.

No abstract

The provision of optimised routing solutions is a priority to generate maximum decreases in the cost of school transport. The aim of this study was to achieve a reduction in existing costs while processing the fare-free transportation of eligible pupil commuters (PCs). The optimisation problem comprised the minimisation of vehicle costs and the total travel time for all pupils. To solve this problem, a heuristic algorithm was developed based on route planning dependent on changes in schools’ starting times so that vehicles can visit a greater number of schools within one route. The algorithm was applied to a municipality in the EU region and the optimised system has been successfully running for 5 years. This study differs from others as it deploys a two-mechanism procedure: the identification of eligible PCs prior to assigning them to bus stops and determining the optimal assignment of school start/finish times for selected schools simultaneously with optimal driving routes and vehicle fleet. After application of the optimisation to the municipality, the total daily mileage of all vehicles was almost 300 km less than the previous un-optimised situation, while the total number of vehicles was reduced by almost 50%.