The selective travelling salesman problem
Discrete Applied Mathematics - Southampton conference on combinatorial optimization, April 1987
The role of adaptive hypermedia in a context-aware tourist GUIDE
Communications of the ACM - The Adaptive Web
Approximation algorithms for time-dependent orienteering
Information Processing Letters
Solving the Orienteering Problem Through Branch-And-Cut
INFORMS Journal on Computing
Traveling Salesman Problems with Profits
Transportation Science
Metaheuristics for the team orienteering problem
Journal of Heuristics
A TABU search heuristic for the team orienteering problem
Computers and Operations Research
Ants can solve the team orienteering problem
Computers and Industrial Engineering
A Personalized Tourist Trip Design Algorithm For Mobile Tourist Guides
Applied Artificial Intelligence
The personal tour planning engine based on genetic algorithm
ICAIT '08 Proceedings of the 2008 International Conference on Advanced Infocomm Technology
Computers and Operations Research
A memetic algorithm for the team orienteering problem
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Design and implementation of a tour planning system for telematics users
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part III
Variable neighborhood search for the orienteering problem
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Algorithms for Itinerary Planning in Multimodal Transportation Networks
IEEE Transactions on Intelligent Transportation Systems
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
A genetic algorithm for shortest path routing problem and the sizing of populations
IEEE Transactions on Evolutionary Computation
SigTur/E-Destination: Ontology-based personalized recommendation of Tourism and Leisure Activities
Engineering Applications of Artificial Intelligence
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This paper addresses the problem of time-dependent tour planning in complex and large urban areas that may be of importance for different groups of people. The problem is determination of chronological sequences of attractive points during a specific period via several modes of transportation system. The proposed approach adopted a nested architecture in which tour planning routine calls multimodal shortest path subroutine to generate an itinerary based on user preferences and restrictions of interesting points. Two adapted genetic algorithms were employed in the engine of both blocks. In these algorithms, chromosomes with variable lengths and particularly defined evolutionary stages are used. The proposed process has been tested over the dataset of city of Tehran. The evaluation consists of preparation of 400 tours with different initial points, start time, and tour durations. It was assumed that just three modes of walking, bus, and subway are used to travel between points of interest. Moreover, some tests are applied to dataset to illustrate the adaptability and time-dependency nature of method. The experimental results and related indices such as optimality ratios show that the proposed algorithm can find optimum tour according to introduced constraints.