Optimal utility customized tourist attraction route planning system

Abstract

According to the method, firstly, based on analysis of a tourist attraction line planning problem, the tourist attraction line planning problem is converted into a traveling salesman problem, a combinatorial optimization problem containing multiple constraint conditions is designed, and various factors in actual touring of tourists are combined, a tourist attraction route planning problem model under the constraint conditions of tourist time, designated entrances and exits and tourist utility is constructed, then ACO is adopted and improved, two kinds of route guiding type information are defined from the two aspects of distance and attraction, distance and attraction ants are correspondingly established, searching is carried out cooperatively, and an optimal route is searched, the judgment standard of the optimal path is changed into the maximum utility rather than the shortest distance, the out-of-pass element is updated by using the utility rather than the distance, ACO solution based on the optimal utility is established, finally, tourist attraction route planning software is developed, the interface is simple and elegant, the function of each module reaches the expected target, and the method is suitable for popularization and application, and the whole system operates efficiently and stably.

Description

technical field [0001] The application relates to a customized tourist attraction route planning system, in particular to a customized tourist attraction route planning system with optimal utility, which belongs to the technical field of tourist attraction route planning. Background technique [0002] With the gradual improvement of the status of the tourism industry, the development of computer technology and mobile information technology, and inspired by the construction and development of smart cities, the concept of smart tourism was proposed. Smart tourism is based on the new generation of information technology to meet the customized needs of tourists and provide high-quality Satisfaction and high-quality service, and the systematic management reform to realize the sharing and effective utilization of tourism resources will provide tourists with information services. [0003] At present, self-guided travel has become the choice of more and more tourists. For self-help...

AI Technical Summary

Problems solved by technology

[0010] Second, some scenic spots have successively introduced equipment such as tour guides, but generally speaking, the functions of electronic tour guide equipment are still in the non-intelligent stage, and it is still far from realizing the function of intelligent tour guides. Itinerary planning services are often highly subjective and can only be used as a reference, and most of them are a single list of tourist attractions, and cannot provide customized route recommendations according to tourists’ preferences. Most of the methods are between cities. Tourist path planning, or the optimal path planning between several scenic spots in the city, and the path planning between scenic spots inside the scenic spot is less involved. Although there are fewer factors considered inside the scenic spot, the time requirements are more stringent. Small changes in the order of tours may have a major impact on tourists' satisfaction. The factors currently considered basically include travel time and travel costs, and the optimization criteria considered are single, rarely involving subjective indicators such as tourists' travel satisfaction and experience values. , and tourists pay more attention to the feeling value they get rather than the shortest path during the tour. The existing technology does not take tourist satisfaction as an optimization index, and its rationality is doubtful;

[0011] Third, the ACO of the existing technology is mainly based on positive feedback, which easily makes ACO fall into a local optimum, which limits the diversity of the search space of the ant system, but there is a contradiction between increasing the search space of the algorithm and increasing the convergence, and it is impossible to control both. The relative importance between them, the solution efficiency is low, and the route planning of tourist attractions cannot achieve the expected results. Some route planning apps are prone to program crashes between the jumps of each page, and cannot generate a reasonable tour route in a short time. Tourists in scenic spots provide route planning services for scenic spots, which rarely involve subjective indicators such as tourists’ travel satisfaction and feeling value, and cannot provide customized route recommendations according to tourists’ preferences. Users cannot plan routes before visiting scenic spots, which is not conducive to easy satisfaction travel experience

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