Intelligent Filter Attractions Based on Multi-objective Programming

Abstract

Family summer travel packages designing should consider the demands of different families, such as the number of people, the cost, the time and the other factors. It is important to decide how to choose the scenic spot in order to make the trip to scenic spots as much as possible, as far as possible. This problem can be abstracted as a multi-objective programming problem. Therefore, we can make use of multi-objective optimization model to filter scenic spots. Keywords-intelligent filter; multi-objective programming model; traveling salesman problem; genetic algorithm This is a classical traveling salesman problem, and we can make use of Genetic Algorithm and other algorithms to solve a specific line of travel. In view of a tourist city, Shanghai for example, there is numerous of scenic spots and several of choices of completing the tour. We can calculate the attractions of some districts in Shanghai and put forward a concept of degree dense according to the Shanghai attractions to partition scenic spots, and then filtered each partition attractions. In this way, we can save calculate and make the calculation to be more operability and practicability. We use Genetic Algorithm to find the optimal route. This method can greatly reduce the amount of calculation, and our solutions are more comprehensive. It can meet the demands of various customers. Different level demands of different family can be divided respectively: (1) there is no cost constraint, but time limitation; (2) there is cost limitation, and a time limitation; (3) there is cost limitation, but no cost restriction. The first and the third are two special circumstances, and the second is a common condition. In this case, different levels of requirement should have different optimal routes. In view of different levels of demand analysis, such as different scenic spot category, natural folk, entertainment and leisure, cultural sports class, we can plan the daily schemes.