Paper Title
Design of a Genetic Algorithm-Based Coupon Advertisement For Electric Vehicles

This paper designs a real-time coupon recommendation service for moving vehicles. Not only database tables are defined but also user interfaces are prototyped for coupon issuers to upload their hot deal information instantaneously. While driving, a traveler retrieves available coupons filtered first by its location and further by the diversity and proximity criteria. To cope with the potentially tremendous computation time stemmed from exploding number of feasible recommendation sets, the genetic algorithm is exploited. Its encoding mechanism specifies coupon categories to which each item belongs, such as restaurants, cafés, charging stations, and the like. In assessing the quality of a feasible solution, the fitness function picks one element in each category, if any, one by one and builds subsets consisting of essential elements and those which are located proximately together. Finally, the set having the maximum economic gain will be provided to the customer. Keywords— Smart Tour, Real-time Coupon Recommendation, Category-based Encoding, Genetic algorithm, Diversity and Proximity Criteria.