The objectives underlying location decisions can be various. Among them, equity objectives have received an increasing attention in recent years, especially in the applications related to the public sector, where fair distributions of accessibility to the services should be guaranteed among users. In the literature a huge number of equality measures have been proposed; then, the problem of selecting the most appropriate one to be adopted in the decision-making processes is crucial. For this reason, many authors focused on the analysis of properties that equality measures should satisfy in order to be considered suitable. Most of the proposed properties are too general and related solely to the mathematical formulation of the measure itself (i.e., simpleness, impartiality, invariance). Hence, they do not give any indications about the behaviour of such measures in the optimization contexts. In this work, we propose some new properties to be associated to equality measures in order to describe characteristics which may be useful to drive optimization procedures in the search of optimal (or near-optimal) solutions. To this aim some empirical analyses have been performed in order to understand the typical behavior of remarkable measures in presence of a uniform distribution of demand points in a regular location spaces
The recent remarkable increase in air passenger traffic has been fostering a considerable congestion of the airport facilities. In this context, traditional procedures employed for check-in operations have been supporting by alternative methods, based on the use of self-service options (kiosks, web services, app for mobile phones, etc). However, even if such innovations are contributing to improve the service level provided to passengers, field investigations suggest that traditional procedures will be employed also in the future, especially for medium and long-haul flights, where baggage dropping is required. For this reason, the passengers allocation problem at check-in counters is attracting growing attention by the scientific community and several decision support tools, involving both optimization and simulation methods, have been proposed. Most of the available approaches aim at deciding the optimal number of check-in counters to be activated, in such a way to balance the operative costs and passengers waiting times. Such approaches assume that the service capacity (in terms of available check-in operators and counters) is given and determined on the basis of physical constraints (related to the available space in the terminal) and of staff scheduling decisions made at a tactical level. The present contribution tries to over
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