New multi-objective optimization model for tourism systems with fuzzy data and new approach developed epsilon constraint method

Tourism is one of the fastest-growing industries in the world and the most significant service sector industry. A fundamental question that can be prompted is how to minimize the total tour cost and, at the same time, design the tour to make the tourists get maximum satisfaction. This paper proposes a new multi-objective optimization model for tourism systems with fuzzy data and new approach developed Epsilon constraint method. We have considered problem modelling in the form of multi-objective optimization in which we can optimize the conflicting goals at the same time. Here we have considered a provider of tour packages that intends to minimize its total costs and, at the same time, maximize the satisfaction of tourists with their packages. In our proposed model, some of the model parameters are fuzzy numbers, so an appropriate algorithm is proposed to solve the multi-objective optimization model. The results can offer constructive suggestions on how to design tours on the part of tourism enterprises and choose a proper tour. One of the advantages of the method used in this article is the simultaneous use of deterministic (certain) variables and fuzzy variables, which is presented as a multi-objective optimization model. Also, a new constraint is added to our model according to the relationship between cost and satisfaction level. Also, to deal with this specific multi-objective optimization model, a new algorithm with new approach Developed Epsilon constraint method is proposed. The proposed algorithm is used in a case study, and in this example, it performed better than the other algorithms.