다목적 환경에서의 ATIS 운영을 위한 $A^*$ 탐색 알고리듬과 유전자 알고리듬의 혼합모형

A Hybrid Model of $A^*$ Search and Genetic Algorithms for ATIS under Multiple Objective Environment

This paper presents a new approach which uses $A^*$ search and genetic algorithms for solving large scale multi-objective shortest path problem. The focus of this paper is motivated by the problem of finding Pareto optimal paths for an advanced traveler information system(ATIS) in the context of intelligent transportation system(ITS) application. The individual description, the decoding rule, the selection strategy and the operations of crossover and mutation are proposed for this problem. The keynote points of the algorithm are how to represent individuals and how to calculate the fitness of each individual. The high performance of the proposed algorithm is demonstrated by computer simulations.