A Hybrid DEA-PSO Model for Improving Tourism Supply Chain Efficiency (Case Study: Kish Free Zone)
Abstract
This study presents a hybrid model based on Data Envelopment Analysis (DEA) and Particle Swarm Optimization (PSO) to enhance the efficiency of the tourism supply chain in the Kish Free Zone. Initially, DEA models are employed to evaluate the relative performance of supply chain units, including hotels, travel agencies, and tourism recreation facilities, identifying their strengths and weaknesses. Subsequently, the PSO algorithm is applied to optimize inputs and outputs to achieve optimal efficiency. The data used in this research were collected through field surveys and relevant tourism industry databases in Kish. The results indicate that the integration of DEA and PSO serves as an effective tool for analyzing and optimizing the tourism supply chain. This approach can assist managerial decision-making by enabling optimal resource allocation and improving overall industry performance. The study introduces an innovative method for enhancing tourism supply chain efficiency, which can be adapted for other tourism destinations as well.
Keywords:
Data envelopment analysis, Particle swarm optimization, Efficiency evaluation, Tourism supply chain, Kish free zoneReferences
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