The largest part of food sales is managed by large food supply chains. However, an alternative system of food distribution focuses on locally produced and sold food that has gotten great attention in the last two decades. The challenges of those new systems, called short food supply chains (SFSC), represent tough market competitions, high distribution and logistics costs, small shipment sizes and so forth. Hence, the SFSC requires corresponding solutions in food distribution that are aligned with the contemporary logistics trends, sustainability and aspects of the new digital era. Using specially developed methodology, based on two different conceptual models, we showed how the SFSC could be designed from the aspects of innovative logistics modes and contemporary information and communication technologies, with the final aim to outline and evaluate different food distribution scenarios towards greater sustainability. The first conceptual model was aimed at the creation of innovative forms of SFSC, in which business process modelling was used in order to design and explore the given situation more thoroughly. For the purposes of conducting a comparative assessment of the distribution models developed in the previous part, the second conceptual model is developed. By using a qualitative approach, this is how the major advantages and challenges of practical implementations in creating sustainable distribution solutions are stated for each scenario.

One of the basic problems of sustainability in modern society is the reduction of waste, particularly when it comes to food. Food waste has negative impacts on different dimensions of sustainability: social (hunger), economic (resource costs), and environmental (resource consumption and waste generation). This paper focuses on waste reduction through improving the inventory management system in the dairy distribution chain by the application of modern information and communication technologies (ICT). The approach is tested and verified in a case study by application of simulation modelling. Two inventory management models are created, and their impact on waste in the distribution part of the supply chain is examined. Model 1 represents the current dairy inventory management system in the supply of retail stores. Model 2 is based on a higher level of information connectivity between participants (RFID product labelling and the appropriate level of information technology), enabling automatic product ordering and changes in inventory management policy. The obtained results confirm that coordinated inventory management, supported by the application of modern ICT, can significantly contribute to the improvement of the sustainability of the food supply chain, and provide an exact quantification of the given contribution in the case of the dairy industry.

Demand forecasting is a fundamental component of efficient supply chain management. An accurate demand forecast is required at several different levels of a supply chain network to support the planning and decision-making process in various departments. In this paper, we investigate the performance of bottom-up, top-down and optimal combination forecasting approaches in a supply chain. We first evaluate their forecast performance by means of a simulation study and an empirical investigation in a multi-echelon distribution network from a major European brewery company. For the latter, the grouped time series forecasting structure is designed to support managers’ decisions in manufacturing, marketing, finance and logistics. Then, we examine the forecast accuracy of combining forecasts of these approaches. Results reveal that forecast combinations produce forecasts that are more accurate and less biased than individual approaches. Moreover, we develop a model to analyse the association between time series characteristics and the effectiveness of each approach. Results provide insights into the interaction among time series characteristics and the performance of these approaches at the bottom level of the hierarchy. Valuable insights are offered to practitioners and the paper closes with final remarks and agenda for further research in this area.

To stay competitive on the constantly changing and demanding market, production systems need to optimize their performance daily. This is particularly challenging in labour-intensive industries, which is characterized by highly volatile customer demand and significant daily variability of available workers. The Uncertainty related to the key production parameters in the industry is causing disruptions in long-term production planning and optimization, which leads to the long lead production times, operational risks and accumulation of inventory. To address these challenges, production systems need to ensure adequate operational production planning and optimization of all variables that are influencing the productivity of their systems on a daily basis. To tackle the problem, this study elaborates the application of discrete event simulations and genetic algorithm, using the Tecnomatix Plant Simulation software, to support decision-making and operational production planning and optimization in the industry. The simulation model developed for this purpose considers: customers demand changes, variable production times, operationally available resources and production batch size, to provide an optimal production sequence with the highest number of produced pieces and the lowest total work in process (WIP) inventory per day. To demonstrate the efficiency of the methodology and prove the benefits of the selected optimization approach, a case study is conducted in the textile factory.

Sustainable development, urban planning, mobility, and transport planning, integrated within the context of sustainable urban mobility, have been central themes in both scientific and applied spheres over the past few decades. In port cities, it becomes particularly essential to tackle sustainability issues given the pollution and noise emanating from ships and other port-related activities. To meet mobility and transportation sustainability needs in the port area, a port should implement measures aligned with a sustainable urban mobility planning (SUMP) approach. However, many ports have thus far achieved limited results in this direction due to the absence of an approach to defining sustainable mobility solutions based on the SUMP approach for an urban area associated with the given port. The overall aim of this paper is to support the development of territorial SUMP for port areas by proposing a methodology that identifies and prioritizes sustainable mobility solutions tailored to a specific port area. The proposed methodology is applied in the Port of Bar (Montenegro) through an appropriate case study. In this case study, the methodological steps are systematically followed, resulting in the practical implementation of the selected mobility solution: the use of a hybrid bus for internal employee transportation within the port area. The undertaken case study underscores the simplicity, practical applicability, and adaptability of the proposed methodology.

The contribution deals with a device, which allows recording values of tensile forces acting on steel ropes. At the same time, this device allows setting of the same values of tensile forces in carrier ropes within multi-rope systems, which are initially unevenly subjected to tension by the...