A study on the multiobjective optimization model for tourism development – Take Shanghai as example

Qian Li, Meiwei Tang and Chengbo Li
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Qian Li: 12634Shanghai University of Finance and Economics, China
Meiwei Tang: 12391Nanjing University of Finance and Economics, China
Chengbo Li: 12688Dongbei University of Finance and Economics, China

Tourism Economics, 2021, vol. 27, issue 4, 762-776

Abstract: This article establishes a multiobjective optimization model for discussing tourism development issues. Tourism direct gross value added (TDGVA), tourism employment (TE) and tourism carbon emissions (TCEs) are integrated in the model, and sets of Pareto solutions are defined. By solving multiobjective optimization model through genetic algorithm, we design three tourism industry structure optimization schemes, namely, the growth-biased scheme, low-carbon emissions-biased scheme and employment-biased scheme. Compared with the actual data for 2012, TDGVA increased by 23.8 billion yuan rising by 14.8% in the growth-biased scheme, TCE fell by 4.97 million tons decreasing by 11.3% in the low-carbon emissions-biased scheme and TE increased by 83.53 thousand jobs increasing by 2% in the employment-biased scheme. The selection of tourism policy depends on the preference of decision makers.

Keywords: multiobjective optimization; tourism added value; tourism carbon emissions; tourism employment (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:sae:toueco:v:27:y:2021:i:4:p:762-776

DOI: 10.1177/1354816620901934

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