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- W2429375105 abstract "In this paper we propose a parallel heuristic to solve a broad formulation of the travel planning problem. Given a set of destinations and a travel time window, our goal is to find a route that produces a budget travel itinerary, involving plane flights, hotels, stays in each destination and departure/arrival times. When the sequence of cities is fixed, the problem is commonly modeled in literature as a time-dependent network and the best itinerary is computed using shortest path algorithms. However, in our formulation, finding the order of cities that minimizes the total cost is also a goal. Therefore, our formulations stand for a Time Dependent Shortest Path Problem (TDSPP) embedded in the NP-Hard Travel Salesman Problem (TSP). Since an exact approach for our problem would be very time consuming depending on the number of cities, we use a parallel Iterated Local Search (ILS) heuristic to search for promising candidate routes in a realistic travel network. We present experimental results on 285 instances and show that our approach takes in average up to 3 minutes to reach solutions in average less than 3% divergent from an exact implementation. Additionally, our method reaches the optimal solution in about 30% of the test cases." @default.
- W2429375105 created "2016-06-24" @default.
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- W2429375105 date "2015-12-01" @default.
- W2429375105 modified "2023-09-26" @default.
- W2429375105 title "A parallel heuristic for the travel planning problem" @default.
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- W2429375105 doi "https://doi.org/10.1109/isda.2015.7489239" @default.
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