Abstract
The paper develops a Multiobjective Optimisation (MOO) model for addressing Capacitated Facility Location Problem (CFLP) in tourism logistics, where two objectives are total of cost and customer service level. Nondominated Sorting Genetic Algorithm II (NSGA II) is used to solve the model. The illustrative case with imaginary data demonstrates that the model can figure out the location of the nodes of tourism logistics network and allocation of these sites, while the total of cost is reduced by up to 56.75% and customer service level is increased by an average of 105%. The distinction of this study compared to the current papers is that our model incorporates both items A and B to the subject matter of tourism logistics, where items A refer to tourism-related products and items B involve personal goods of tourists. The model established is limited with one assumption and one limitation which are associated with Vehicle Routing Problem (VRP) and the boundary of tourism logistics activity. Therefore, further research for the elimination of these limits is recommended.
Highlights
Tourism Logistics (TL) is defined as a space- and time-related transformation of material, people, information, energy, waste, knowledge, and capital aiming to provide the quality tourism services at the lowest total of costs (TOC) [1,2,3,4,5,6,7,8,9,10,11]
Jin et al [12] argue that tourism logistics ought to handle two types of goods; one is items A which can be traded in tourism industry such as food and hotel supplies and the other one is items B which belong to and are carried by a tourist such as personal luggage
Due to the essential significance of both TOC and customer service level (CSL) for tourism logistics, we have the following questions: in a tourism logistics network, where the facility locations should be placed, which facilities are connected, and how much capacity ought to be for each site selected, in order to minimise TOC and maximise CSL simultaneously? In this regard, the question is associated with a type of Multiobjective Optimisation (MOO) related to Capacitated Facility Location Problem (CFLP)
Summary
Tourism Logistics (TL) is defined as a space- and time-related transformation of material, people, information, energy, waste, knowledge, and capital aiming to provide the quality tourism services at the lowest total of costs (TOC) [1,2,3,4,5,6,7,8,9,10,11]. Jin et al [12] argue that tourism logistics ought to handle two types of goods; one is items A which can be traded in tourism industry such as food and hotel supplies and the other one is items B which belong to and are carried by a tourist such as personal luggage. They point out that, from the perspective of systems approach, the basic goal of tourism logistics is to support a highly free separation and mergence between tourists and items.
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