PROCUREMENT OPTIMIZATION BY SELECTING EFFICIENT SUPPLIERS USING DEA-FUCOM-COCOSO APPROACH AND SOLVING ORDER ALLOCATION PROBLEM

Procurement logistics is one of the most important segments of the supply chain and one of the key factors of a company’s competitiveness. For that reason, many companies strive for constant optimization of this segment of the supply chain, both in terms of costs and in terms of time, reliability, etc. The aim of this paper is to develop a new approach based on DEA-FUCOM-CoCoSo methods that aim to select efficient suppliers. The developed model was tested on the data of one trading company. The DEA method was used in order to select only efficient ones from 29 observed in this paper. The FUCOM method was used to determine the weights of the 9 observed criteria used in the CoCoSo method for evaluation of 6 efficient suppliers. The results of the application of this method determined the final rank of suppliers, after which only the first 3 suppliers were considered. At the very end, a model for solving the problem of order allocation is defined in order to determine from which supplier it is necessary to order goods and in what quantity. By applying the defined model, the quantities that need to be ordered from certain suppliers in order to meet the demand on the market are obtained. Based on the results, the developed approach showed the possibility of large application not only on the observed example but also on a larger problem

MEASURING EFFICIENCY CHANGE IN TIME APPLYING MALMQUIST PRODUCTIVITY INDEX: A CASE OF DISTRIBUTION CENTRES IN SERBIA

In the last decade, more and more attention has been paid to the efficiency of logistics systems not only in the literature but also in practice. The reason is the huge savings that can be achieved. In a very dynamic market with environmental changes distribution centers have to realize their activities and processes in an efficient way. Distribution centers connect producers with other participants in the supply chain, including end-users. The main objective of this paper is to develop a DEA model for measuring distribution centers’ efficiency change in time. The paper investigates the impact of input and output variables selection on the resulting efficiency in the context of measuring the change in efficiency over time. The selection of variables on the one hand is a basic step in applying the DEA method. On the other hand, the number of basic and derived indicators that are monitored in real systems is increasing, while the percentage of those used in the decision-making process is decreasing (less than 20%). The developed model was tested on the example of a retail chain operating in Serbia. The main factors changing the efficiency have been identified, as well as the corresponding corrective actions. For measuring efficiency change in time Malmquist productivity index is used. The developed approach could help managers in the decision-making process and also represents a good basis for further research

Automated mapping of climatic variables using spatio-temporal geostatistical methods

Javno dostupni meteorološki podaci, kako sa stanica tako i iz daljinske detekcije, korišćeni su za prostorno vremensku interpolaciju temperature vazduha iznad površine Zemlje. Zastupljenost i pogodnost javno dostupnih podataka je ocenjena, kroz tri aspekta kontrole kvaliteta: (a) zastupljenost u geografskom i prostornom domenu, (b) zastupljenost u karaktestičnom prostoru (feature space; bazirano na MaxEnt metodi), kao i (c) pogodnost korišćenja podataka za prostorno-vremensku predikciju (na osnovu kros-validacije prostorno-vremnskog regresionog kriginga). Rezultati pokazuju da je kombinovani set podataka (GSOD i ECA&D) značajno klasteriran i u geografskom i u karakterističnom prostoru. Uprkos klasteriranju, preliminarni rezultati globalne interpolacije primenom prostorno-vremenskog regresionog kriginga koristeći merenja sa stanica i snimke daljinske detekcije su pokazali da se tako mogu dobiti precizne globalne karte dnevne temperature. Oko 9000 stanica kombinovanog seta podataka (GSOD i ECA&D) je korišćeno za prostorno-vremensko geostatističko modeliranje i predikciju dnevnih temperatura u rezoluciji 1 km, iznad površine Zemlje. Za predikciju srednjih, minimalnih i maksimalnih temperatura korišćen je regresioni kriging uz pomoćne prediktore: MODIS LST 8-dnevni snimci, topografski lejeri (DEM i TWI) i geometrijski temperaturni trend. Model i predikcija se odnose na 2011 godinu, ali ista metodologija bi se mogla primeniti od 2001 godine do danas (od kada su dostupni MODIS snimci). Rezultati pokazuju da je prosečna tačnost predikcije za srednju, minimalnu i maksimalnu temperaturu vazduha oko ±2°C za oblasti gusto pokrivene stanicama i između ±2°C i ±4°C za oblasti koje su slabo pokrivene stanicama. Najniža tačnost predikcije je dobijena u planinskim predelima i na Antartiku, oko 6°C. R softverski paket, meteo, je razvijen kao resenje za automatsko kartiranje. Razvijen je i paket plotGoogleMaps za automatsku vizuelizaciju na Web-u, koristeći Google Maps API.Publicly available global meteorological data sets, from ground stations and remote sensing, are used for spatio-temporal interpolation of air temperature data for global land areas. Publicly available data sets were assessed for representation and usability for global spatio-temporal analysis. Three aspects of data quality were considered: (a) representation in the geographical and temporal domains, (b) representation in the feature space (based on the MaxEnt method), and (c) usability i.e. fitness of use for spatio-temporal interpolation (based on cross-validation of spatio-temporal regression-kriging models). The results show that clustering of meteorological stations in the combined data set (GSOD and ECA&D) is significant in both geographical and feature space. Despite the geographical and feature space clustering, preliminary tested global spatio-temporal model using station observations and remote sensing images, shows this method can be used for accurate mapping of daily temperature. Around 9000 stations from merged GSOD and ECA&D daily meteorological data sets were used to build spatio-temporal geostatistical models and predict daily air temperature at ground resolution of 1 km for the global land mass. Predictions were made for the mean, maximum and minimum temperature using spatio-temporal regression-kriging with a time series of MODIS 8 day images, topographic layers (DEM and TWI) and a geometrical temperature trend as covariates. The model and predictions were built for the year 2011 only, but the same methodology can be extended for the whole range of the MODIS LST images (2001–today). The results show that the average accuracy for predicting mean, maximum and minimum daily temperatures is RMSE = ± 2°C for areas densely covered with stations, and between ± 2°C and ± 4°C for areas with lower station density. The lowest prediction accuracy was observed in highlands (> 1000 m) and in Antarctica with a RMSE around 6°C. Automated mapping framework is developed and implemented as R package meteo. Likewise, package plotGoogleMaps for automated visualisation on the Web, base on Google Maps API is developed

Supply Chain RFID Solution Evaluation Applying AHP and FAHP Methods: A Case Study of the Serbian Market

There has been a recent years tendency for replacing traditional supply chain data identifying and collecting systems with RFID (Radio Frequency Identification) technologies. There are different RFID solutions on the market and it is crucial to choose the solution that best suits the set of goals and desired scenarios. The choice of solution depends on a whole range of different factors and criteria. The present paper develops multi-criteria evaluation models based on the AHP (Analytic Hierarchy Process) and FAHP (Fuzzy Analytic Hierarchy Process) approach. There are no papers in the literature that solve the mentioned problem in this way, on a real example. Three RFID solutions are defined referring to different data identification levels in supply chains, namely: product level, level of packaging and the level of the pallet. Solutions are evaluated, and rated in relation to four criteria: investments, costs, participants\u27 visibility and participants\u27 privacy protection in supply chains. Developed models are tested and applied via a case study conducted in the Serbian market. The model is an excellent basis for decision-making in practice and for researchers in the literature, while with certain modifications, it can be used for other similar problems

Kartiranje međa poljoprivrednih parcela super rezolucijom na temelju lokaliziranoga parcijalnog razdvajanja

Operational mapping of crop/agricultural parcel boundaries is a challenging task. It should be efficient and inexpensive process resulting with data useful for wide range of purposes. Hard classification of medium resolution (>15 m, 15 m, <30 m) mogla bi biti rješenje, no prostorna rezolucija snimaka nije dovoljna za mnoge primjene. U ovom radu predstavljena je blaga klasifikacija podataka daljinskog istraživanja srednje rezolucije te kartiranja žitnih parcela super rezolucije. Metoda je razvijena na temelju lokaliziranoga parcijalnog razdvajanja procjenjujući spektar krajnjeg člana i cilja i pozadine. Rezultat je bio podvrgnut razmjeni piksela kao tehnike kartiranja super rezolucijom. Ispitivanje se provodi na stvarnim snimkama Landsat ETM+. Metoda je vrednovana kvantitativno, a rezultati pokazuju značajnu točnost u usporedbi s kartiranjem iz originalnih podataka daljinskog istraživanja

Modelling the spatial distribution of Vojvodina's population by using dasymetric method

Cartographic presentation of heterogeneity/homogeneity in the spatial distribution of population is still a major problem in modern geography, and other geo-sciences as well. The traditional method of thematic or choropleth mapping rarely gives satisfactory results. This paper analyzes the applicability of dasymetric mapping method for the modelling of spatial distribution of population. Although it is a relatively old method, it becomes widely used following the development of computer technology, GIS and satellite imagery, and its applicability is increasing in social, economic and other sciences and disciplines. After showing the basis and development of dasymetric mapping, the authors present possible application of this method in the population distribution modelling of Vojvodina