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MULTIMODAL DAILY TRAVEL PLANNER

R. Kitamura

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Abstract

This paper introduces a new travel planning assistance tool, the Travel Itinerary Planner, which offers the following unique features: (i) it is multimodal, (ii) it builds an itinerary for multiple trips and visits, (iii) it incorporates many types of constraints associated with travel and visits, and (iv) it interacts with the user to measure his/her preferences and updates itineraries until a satisfactory one is found by the user. In this paper, these unique features are first discussed in detail. Following this, each component of the Planner is described. Also discussed are the algorithms used to find the best routes between locations to visit, to build alternative itineraries, and to update preference weights. A brief discussion on future research directions concludes the paper. For the covering abstract see IRRD E102946.

About this research paper

What this paper is about

This paper introduces a new travel planning assistance tool, the Travel Itinerary Planner, which offers the following unique features: (i) it is multimodal, (ii) it builds an itinerary for multiple trips and visits, (iii) it incorporates many types of constraints associated with travel and visits, and (iv) it interacts with the user to measure his/her preferences and updates itineraries until a satisfactory one is found by the user. In this paper, these unique features are first discussed in detail. Following this, each component of the Planner is described. Also discussed are the algorithms used to find the best routes between locations to visit, to build alternative itineraries, and to update preference weights. A brief discussion on future research directions concludes the paper. For the covering abstract see IRRD E102946.

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Available abstract

This paper introduces a new travel planning assistance tool, the Travel Itinerary Planner, which offers the following unique features: (i) it is multimodal, (ii) it builds an itinerary for multiple trips and visits, (iii) it incorporates many types of constraints associated with travel and visits, and (iv) it interacts with the user to measure his/her preferences and updates itineraries until a satisfactory one is found by the user. In this paper, these unique features are first discussed in detail. Following this, each component of the Planner is described. Also discussed are the algorithms used to find the best routes between locations to visit, to build alternative itineraries, and to update preference weights. A brief discussion on future research directions concludes the paper. For the covering abstract see IRRD E102946.

Key concepts: Planner, TRIPS architecture, Computer science, Preference, Measure (data warehouse), Component (thermodynamics), Operations research, Transport engineering

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