9 research outputs found
Exploring the association between time series features and forecasting by temporal aggregation using machine learning
No full textWhen a forecast of the total value over several time periods ahead is required, forecasters are presented
with two temporal aggregation (TA) approaches to produce required forecasts: i) aggregated forecast (AF)
or ii) aggregate data using non-overlapping temporal aggregation (AD). Often, the recommendation is to
aggregate data to a frequency relevant to the decision the eventual forecast will support and then produce the forecast. However, this might not be always the best choice and we argue that both AF and
AD approaches may outperform each other in different situations. Moreover, there is a lack of evidence
on what indicators may determine the superiority of each approach. We design and execute an empirical
experiment framework to first explore the performance of these approaches using monthly time series of
M4 competition dataset. We further turn the problem into a classification supervised learning by constructing a database consisting of features of each time series as predictor and model class labelled as
AF/AD as response/outcome. We then build machine learning algorithms to investigate the association
between time series features and the performance of AF and AD. Our findings suggest that both AF
and AD approaches may not consistently generate accurate results for every individual series. AF is
shown to be significantly better than AD for the monthly M4 time series, especially for longer horizons.
We build several machine learning approaches using a set of extracted time series features as input to
predict accurately whether AD or AF should be used. We find out that Random Forest (RF) is the most
accurate approach in correctly classifying the outcome assessed both by statistical measures such as misclassification error, F-statistics, area under the curve, and a utility measure. The RF approach reveals that
curvature, nonlinearity, seas_pacf, unitroot_pp, mean, ARCHM.LM, Coefficient of Variation, stability, linearity, and max_level_shif are among the most important features in driving the predictions of the model.
Our findings indicate that the strength of trend, ARCH.LM, hurst, autocorrelation lag 1, unitroot_pp, and
seas_pacf may favour AF approach, while lumpiness, entropy, nonlinearity, curvature, and strength of
seasonality may increase the chance of AD performing bet
Identifying the Barriers for Development of Inland Waterway Transport: a Case Study
No full textInland waterway transport represent environmentally friendly transport mode accompanied with other potential benefits, such as increased transport safety and increased cost savings. In order to encourage further development of inland waterway transport in this paper focus is set on the identification of the barriers that limit and prevent development of inland waterway transport. More specifically, emphasis is placed on the barriers that are preventing the cargo shifting from land to waterway transport system. Research conducted in case of Republic of Serbia investigates several barriers which are classified in four main categories: goods, logistics, infrastructure, framework conditions. Framework conditions barriers are further subdivided and classified in four subcategories: political/legal, environment, economy, technology. Results indicate that the most significant negative influence on the further development of the inland waterway transport in Serbia comes from the political/legal barriers. This result implies that the government need to pay more attention to development of inland waterway transport, as well as to make more effort to enhance the cooperation with stakeholders
Identifying the Barriers for Development of Inland Waterway Transport: a Case Study
No full textInland waterway transport represent environmentally friendly transport mode accompanied with other potential benefits, such as increased transport safety and increased cost savings. In order to encourage further development of inland waterway transport in this paper focus is set on the identification of the barriers that limit and prevent development of inland waterway transport. More specifically, emphasis is placed on the barriers that are preventing the cargo shifting from land to waterway transport system. Research conducted in case of Republic of Serbia investigates several barriers which are classified in four main categories: goods, logistics, infrastructure, framework conditions. Framework conditions barriers are further subdivided and classified in four subcategories: political/legal, environment, economy, technology. Results indicate that the most significant negative influence on the further development of the inland waterway transport in Serbia comes from the political/legal barriers. This result implies that the government need to pay more attention to development of inland waterway transport, as well as to make more effort to enhance the cooperation with stakeholders
Reducing Food Waste in the Retail Supply Chains by Improving Efficiency of Logistics Operations
No full textOne 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
Forecasting hierarchical time series in supply chains: an empirical investigation
No full textDemand 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
Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply Chain
No full textDemand forecasting is one of the key activities
in planning the freight flows in supply chains, and
accordingly it is essential for planning and scheduling
of logistic activities within observed supply chain. Accurate
demand forecasting models directly influence the decrease
of logistics costs, since they provide an assessment
of customer demand. Customer demand is a key component
for planning all logistic processes in supply chain,
and therefore determining levels of customer demand is
of great interest for supply chain managers. In this paper
we deal with exactly this kind of problem, and we develop
the seasonal Autoregressive IntegratedMoving Average (SARIMA)
model for forecasting demand patterns of a major
product of an observed beverage company. The model is
easy to understand, flexible to use and appropriate for assisting
the expert in decision making process about consumer
demand in particular periods
Solutions for More Sustainable Distribution in the Short Food Supply Chains
No full textThe 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
Sustainable Urban Mobility Planning in the Port Areas: A Case Study
No full textSustainable 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
Incidence of severe critical events in paediatric anaesthesia (APRICOT): a prospective multicentre observational study in 261 hospitals in Europe
No full textBackground Little is known about the incidence of severe critical events in children undergoing general anaesthesia in Europe. We aimed to identify the incidence, nature, and outcome of severe critical events in children undergoing anaesthesia, and the associated potential risk factors. Methods The APRICOT study was a prospective observational multicentre cohort study of children from birth to 15 years of age undergoing elective or urgent anaesthesia for diagnostic or surgical procedures. Children were eligible for inclusion during a 2-week period determined prospectively by each centre. There were 261 participating centres across 33 European countries. The primary endpoint was the occurence of perioperative severe critical events requiring immediate intervention. A severe critical event was defined as the occurrence of respiratory, cardiac, allergic, or neurological complications requiring immediate intervention and that led (or could have led) to major disability or death. This study is registered with ClinicalTrials.gov, number NCT01878760. Findings Between April 1, 2014, and Jan 31, 2015, 31â127 anaesthetic procedures in 30â874 children with a mean age of 6·35 years (SD 4·50) were included. The incidence of perioperative severe critical events was 5·2% (95% CI 5·0â5·5) with an incidence of respiratory critical events of 3·1% (2·9â3·3). Cardiovascular instability occurred in 1·9% (1·7â2·1), with an immediate poor outcome in 5·4% (3·7â7·5) of these cases. The all-cause 30-day in-hospital mortality rate was 10 in 10â000. This was independent of type of anaesthesia. Age (relative risk 0·88, 95% CI 0·86â0·90; p<0·0001), medical history, and physical condition (1·60, 1·40â1·82; p<0·0001) were the major risk factors for a serious critical event. Multivariate analysis revealed evidence for the beneficial effect of years of experience of the most senior anaesthesia team member (0·99, 0·981â0·997; p<0·0048 for respiratory critical events, and 0·98, 0·97â0·99; p=0·0039 for cardiovascular critical events), rather than the type of health institution or providers. Interpretation This study highlights a relatively high rate of severe critical events during the anaesthesia management of children for surgical or diagnostic procedures in Europe, and a large variability in the practice of paediatric anaesthesia. These findings are substantial enough to warrant attention from national, regional, and specialist societies to target education of anaesthesiologists and their teams and implement strategies for quality improvement in paediatric anaesthesia. Funding European Society of Anaesthesiology
