Rural tourism destination competitiveness: Portugal vs Belarus

This research presents a study aimed to evaluate the performance and competitiveness of tourist destinations in Portugal and Belarus within regions. The evaluation was performed under an analytical tool, Market Share Analysis proposed by Faulkner (1997). In addition, it was used some descriptive statistics. The conducted analysis concluded, with respect to the evolution of the destinations tourism that Açores Island is the most prosperous market for the majority of countries, because most countries staid in the zone of Performing market. North, Lisbon and Algarve regions are maturity markets for the most countries, because they stay in Stagnant markets zone. Centre and Alentejo regions could be attributed Emerging markets for the majority of countries once are developing markets. The major market share is occupied by Portugal practically for all regions, except islands. It is also necessary to underline, that the research was made only within two years (2013 and 2014), because of the lack of necessary information in previous years. In the case of Belarus, it could be mentioned, that rural market of this country is developing (but still mostly with neighbour countries), because the number of entities, participating in rural tourism is growing as the number of foreign tourists.

Model predictive control applied to a supply chain management problem

Supply chains are ubiquitous in any commercial delivery systems. The exchange of goods and services, from different supply points to distinct destinations scattered along a given geographical area, requires the management of stocks and vehicles fleets in order to minimize costs while maintaining good quality services. Even if the operating conditions remain constant over a given time horizon, managing a supply chain is a very complex task. Its complexity increases exponentially with both the number of network nodes and the dynamical operational changes. Moreover, the management system must be adaptive in order to easily cope with several disturbances such as machinery and vehicles breakdowns or changes in demand. This work proposes the use of a model predictive control paradigm in order to tackle the above referred issues. The obtained simulation results suggest that this strategy promotes an easy tasks rescheduling in case of disturbances or anticipated changes in operating conditions. © Springer International Publishing Switzerland 2017