This paper explores the differences in the quality perception of coffee among different participants in the supply chain management of coffee production. Rather, the aim of this paper was to answer the question of whether a particular level of coffee quality is the same for all participants in the supply chain. Also, we wanted to respond to the issue of whether all participants in the supply chain equally valued its characteristic. As a possible remedy to the problem, two-stage PCA-Idistance approach has been performed. The results have shown that there are indeed differences in the quality perception of coffee among different participants in the supply chain. Also, we proposed framework for emphasizing significant components for respective participant, and within crucial quality characteristics. Therein, we determined the most significant component which encompasses following set of characteristics of the coffee supply chain for distributor: the coffee inventory turnover ratio, producer satisfaction with distributor services, customer satisfaction (retail) with distributor services. Likewise, same procedure was done for producer and analysis pointed out following quality characteristics: the coffee's country of origin, the manufacture date, the expiry date, storage cost of the final product, customs procedures, delays in procurement, and the temperature of at which the coffee is roasted.

This paper presents an inventory control problem in a private pharmaceutical distribution company from the Republic of Serbia. The company realizes that distribution within nine neighbouring countries and inventory control in the pharmaceutical supply chain is centralized. In order to constitute a conceptual model of the problem, we propose the modern control theory concept. The conceptual model is based on the specific practical assumptions and constraints of the supply chain. Thereafter, a dynamic discrete mathematical model of inventory control is formulated to reflect elements of the system and their relations. The model considers multiple pharmaceutical products, variable lead time, realized stochastics and deterministic demand, and different ordering policies (Lot for Lot and Fixed Order Quantity). Deterministic demand is represented as a sales forecast for each product per month, while stochastic demand is generated as a random variation of sales forecast in a range of ±20%. Two objective functions are defined as the maximization of the difference between planned average inventory level and realized average inventory level, and the minimization of stock-out situations. We develop a procedure for the determination of reorder points and the number of deliveries to achieve proposed objective functions. The model overcomes shortages of theoretically-based distribution requirements planning models and offers solutions to the limitations in inventory control practice. Real-life data, collected over two years, are used for the validation of the proposed model and the solution procedure. Numerical examples illustrate the model application and behaviour.

This paper considers the well-known static time-continuous multiproduct economic order quantity (EOQ) based inventory management problem with the storage space constraints. This problem is modelled as a combinatorial optimization problem in the corresponding dynamic discrete time system control process. In order to solve this problem approximately, we developed two heuristics: a special heuristic based on a local search technique and a metaheuristic procedure based on the variable neighbourhood search principle. The efficiency of two heuristics is preliminary examined and compared on several randomly generated instances with the same number of products.

Deriving from insights gained in a concrete empirical quantitative modelling research, the aim of the paper is to present the methodology and results of a Packaging Waste (PW) logistics exploratory study that was conducted in cooperation with a leading southeastern European retail chain company. PW Reverse Logistics (RL) is specific, but an integral part of retail operations and can also represent significant logistics and transportation costs concerns. In our research, we have, with a simulation model, been able to reduce the number of tonne-kilometres for 55% which represents significant cost reduction. The study scope focuses on the RL of industrial PW as the handling object of interest in retail, decoupled from the possible returns flow of non-food items and waste generated on premise by shoppers and employees, classified as non-industrial. It introduces an analytical framework, which has been tested and applied to a real case problem.

Present-day airline industry is quite a competitive field and crew scheduling represents one of the crucial problems due to significant impact on the airline’s cost. The crew scheduling problem is based on the assignment of crew members to operate different tasks of route. The main goal of this paper is to provide an analysis and a solution to one of the biggest problems detected on a small airport in the Serbia - the problem of ground crew scheduling. The paper presents the main characteristics, goals and limitations of a real-life problem identified at this small airport. In order to solve the problem, we developed a dynamic discrete simulation model. The model is developed in a spreadsheet environment of Microsoft Excel. Some of the main limitations found in the development of the model are strong constraints and multiple goals. The model presented in the paper is designed as a useful management tool for smaller airports and is aimed at the improvement of operative processes.