Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling

Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling

A constrained optimization model and an iterative optimization algorithm based on PSO are designed for rural leisure tourism passenger flow scheduling. Compared with the traditional tourist dispatching scheme, this model maximizes the overall tourist experience and operation profit of the whole regi...

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Main Authors: Fang Su, Chengrui Duan, Ruopeng Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Adaptive algorithm
optimization model
particle swarm optimization
rural leisure tourism
tourist scheduling
Online Access:https://ieeexplore.ieee.org/document/9133395/
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spelling doaj-ee576fe2cd46469d86e2f37dfbca9d822021-03-30T02:20:01ZengIEEEIEEE Access2169-35362020-01-01812529512530510.1109/ACCESS.2020.30071809133395Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow SchedulingFang Su0https://orcid.org/0000-0003-0506-6765Chengrui Duan1https://orcid.org/0000-0002-3149-861XRuopeng Wang2https://orcid.org/0000-0002-3399-3649School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaSchool of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaSchool of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaA constrained optimization model and an iterative optimization algorithm based on PSO are designed for rural leisure tourism passenger flow scheduling. Compared with the traditional tourist dispatching scheme, this model maximizes the overall tourist experience and operation profit of the whole region on the base of protection of tourists' travel experience and the interests of operators in the dispatching spots. Simulations and comparisons are taken to evaluate the feasibility and effectiveness of the model and the optimization. The simulation results show that compared with the shortest-distance-based traffic scheduling scheme and the gravity-model-based scheme, the new model and optimization could meet the requirements of the rural leisure tourists dispatching and bring better tourist experience and tourism profit.https://ieeexplore.ieee.org/document/9133395/Adaptive algorithmoptimization modelparticle swarm optimizationrural leisure tourismtourist scheduling
collection DOAJ
language English
format Article
sources DOAJ
author Fang Su
Chengrui Duan
Ruopeng Wang
spellingShingle Fang Su
Chengrui Duan
Ruopeng Wang
Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling
IEEE Access
Adaptive algorithm
optimization model
particle swarm optimization
rural leisure tourism
tourist scheduling
author_facet Fang Su
Chengrui Duan
Ruopeng Wang
author_sort Fang Su
title Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling
title_short Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling
title_full Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling
title_fullStr Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling
title_full_unstemmed Optimization Model and Algorithm Design for Rural Leisure Tourism Passenger Flow Scheduling
title_sort optimization model and algorithm design for rural leisure tourism passenger flow scheduling
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description A constrained optimization model and an iterative optimization algorithm based on PSO are designed for rural leisure tourism passenger flow scheduling. Compared with the traditional tourist dispatching scheme, this model maximizes the overall tourist experience and operation profit of the whole region on the base of protection of tourists' travel experience and the interests of operators in the dispatching spots. Simulations and comparisons are taken to evaluate the feasibility and effectiveness of the model and the optimization. The simulation results show that compared with the shortest-distance-based traffic scheduling scheme and the gravity-model-based scheme, the new model and optimization could meet the requirements of the rural leisure tourists dispatching and bring better tourist experience and tourism profit.
topic Adaptive algorithm
optimization model
particle swarm optimization
rural leisure tourism
tourist scheduling
url https://ieeexplore.ieee.org/document/9133395/
work_keys_str_mv AT fangsu optimizationmodelandalgorithmdesignforruralleisuretourismpassengerflowscheduling
AT chengruiduan optimizationmodelandalgorithmdesignforruralleisuretourismpassengerflowscheduling
AT ruopengwang optimizationmodelandalgorithmdesignforruralleisuretourismpassengerflowscheduling
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