Abstract
The Orienteering Problem (OP) is a routing problem which has many applications in logistics, tourism and defense. Given a set of nodes, where each node represents a Point of Interest (POI), the orienteering problem aims to design a tour leaving from a starting POI, visiting a subset of POIs and finally arriving at the ending POI. The objective of the problem is to maximize the total score of the visited POIs while the total travel time and the total cost of the route do not exceed two predefined thresholds. Each POI is characterized by a score, a position, a visit time, and a time window in which the POI can be visited. This problem is often investigated to develop tourism trip planning mobile applications. Usually these apps must be able to generate good solutions in few seconds. Therefore, the use of efficient heuristic approaches to find good quality solutions is needed. In this paper we present a genetic algorithm framework combined with some local search operators to deal with the analyzed problem.
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Ciancio, C., De Maio, A., Laganà , D., Santoro, F., Violi, A. (2018). A Genetic Algorithm Framework for the Orienteering Problem with Time Windows. In: Daniele, P., Scrimali, L. (eds) New Trends in Emerging Complex Real Life Problems. AIRO Springer Series, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-00473-6_20
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DOI: https://doi.org/10.1007/978-3-030-00473-6_20
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