Intelligent Engineering Systems through Artificial Neural Networks
37 Applying Metaheuristic Approach to Three-Dimensional Tour Guide Allocation Problem
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A large number of studies has applied a metaheuristic approach to a variety of combinatorial problems. One of the areas where many researchers have used metaheuristic approach is the human resource allocation problem in the tourism industry. In the tourism industry, minimizing costs for tour guides is one of the most important issues. However, there are many constraints to consider when applying a metaheuristic approach to solving this problem.
The purpose of this study is to consider cost minimization of tour guides. While minimizing costs, tour guide language skills, tour knowledge, and intercity transportation costs related to the places where the assigned tour starts should be considered. Moreover, tourist language needs are often ignored in a real-world tour guide allocation. So, tourist language preferences should be satisfied as much as possible. Since dealing with many constraints can be difficult when applying optimum-seeking approaches, this study will apply a well-known metaheuristic approach, genetic algorithm, for solving a three-dimensional (tour, tour guide, and tourist) tour guide allocation problem. As a result, this study shows an optimum tour guide schedule satisfying tourist preferences for type of tour and languages by using multistage decision-based genetic algorithm.