Dijkstra’s Algorithm to Find Shortest Path of Tourist Destination in Bali

Fitriansyah, Aswin; Parwati, N. W.; Wardhani, Dyah Rhetno; Kustian, Nunu

doi:10.1088/1742-6596/1338/1/012044

Cited by 12 publications

(7 citation statements)

References 2 publications

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“…In tourism research, shortest-path algorithms such as the Dijkstra and A* algorithms have typically been used to plan tour routes with the shortest traveling distances. They have the benefits of being easily accessed and applied [40][41][42]. In addition, the shortestpath algorithms were also constrained by tourism factors such as features and spatial attributes.…”

Section: Selecting and Confirming Of The Control Algorithmsmentioning

confidence: 99%

Tour-Route-Recommendation Algorithm Based on the Improved AGNES Spatial Clustering and Space-Time Deduction Model

Zhou

Tian

2022

IJGI

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This study designed a tour-route-planning and recommendation algorithm that was based on an improved AGNES spatial clustering and space-time deduction model. First, the improved AGNES tourist attraction spatial clustering algorithm was created. Based on the features and spatial attributes, city tourist attraction clusters were formed, in which the tourist attractions with a high degree of correlation among attributes were gathered into the same cluster. It formed the precondition for searching tourist attractions that would match tourist interests. Using tourist attraction clusters, this study also developed a tourist attraction reachability model that was based on tourist-interest data and geospatial relationships to confirm each tourist attraction’s degree of correlation to tourist interests. A dynamic space-time deduction algorithm that was based on travel time and cost allowances was designed in which the transportation mode, time, and costs were set as the key factors. To verify the proposed algorithm, two control algorithms were chosen and tested against the proposed algorithm. Our results showed that the proposed algorithm had better results for tour-route planning under different transportation modes as compared to the controls. The proposed algorithm not only considered time and cost allowances, but it also considered the shortest traveling distance between tourist attractions. Therefore, the tourist attractions and tour routes that were suggested not only met tourist interests, but they also conformed to the constraint conditions and lowered the overall total costs.

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Section: Selecting and Confirming Of The Control Algorithmsmentioning

confidence: 99%

Tour-Route-Recommendation Algorithm Based on the Improved AGNES Spatial Clustering and Space-Time Deduction Model

Zhou

Tian

2022

IJGI

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“…The greedy approach means selecting the option or solution that appears to be the greatest at the time. [12]. It merely means selecting the option or solution that appears to be the greatest at the time.…”

Section: B Shortest Path Algorithmmentioning

confidence: 99%

“…The robots must take the shortest possible path to collect/deliver the products to avoid time loss and save energy [26]. Therefore, path-finding algorithms such as Greedy [12] and A* [13] were used to find the shortest path. Since CPS interact with the environment, another problem that may be encountered is the possibility of robots hitting any obstacle that may come their way in the warehouse.…”

Section: Introductionmentioning

confidence: 99%

Towards developing a cyber-physical warehouse system for automated order-picking for online shopping

Alhas¹,

Oruç²,

Usta³

et al. 2022

Communication Papers of the 17th Conference on Computer Science and Intelligence Systems

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In recent years, Cyber-Physical Systems (CPS) have been studied in various application areas. Since there are many robots that need to implement both physical and cyber sides, interact with each other and the environment, and the system has to cope with many faced difficulties, a warehouse system for automated order-picking for online shopping seems to be very suitable for being modeled and implemented as CPS. In this study, the planning and control of mobile robots in a store warehouse is defined from the perspectives of obstacle avoidance, collision detection, and solving the shortest path problem. Accordingly, a simulation environment is designed and a layered CPS development model is proposed. In the simulation environment, both object avoidance and collision detection algorithms are introduced and implemented, different shortest path-finding algorithms are adapted and implemented and their performances are evaluated.

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“…Thirteen criteria were chosen for a multicriteria evaluation of the region's tourism potential. The result of AHP method weight scoring showed the internal potential is more important than the external potential, and the multicriteria assessment of regional tourism potential showed that the Central Highlands have several interesting destinations [5,22,23].…”

Section: Related Workmentioning

confidence: 99%

A Novel Urban Tourism Path Planning Approach Based on a Multiobjective Genetic Algorithm

Damos

Zhu

et al. 2021

IJGI

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One of the most important variables that leads to effective individual and group tours is the tourism route planning approach, which enables tourists to engage with tourism with ease, speed, and safety. However, current methods of designing tourist routes have some glitches, such as relying only on external objectives to find the best route. In this paper, a novel urban tourism path planning method based on a multiobjective genetic algorithm is proposed. The main goal of this paper is to enhance the accuracy of the genetic algorithm (GA) by adopting new parameters and selecting the optimal tourism path by combining external and internal tourist site potentials. Moreover, the GA and analytical hierarchy process (AHP) were used in our proposed approach to evaluate urban tourism route planning under multiple conflicting objectives. To visualize and execute the proposed approach, the geographic information system (GIS) environment was used. Our suggested approach has been applied to develop the tourist road network of Chengdu City in China. Compared with existing tourism path planning approaches, our proposed approach is more accurate and straightforward than other approaches used to choose routes.

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Dijkstra’s Algorithm to Find Shortest Path of Tourist Destination in Bali

Cited by 12 publications

References 2 publications

Tour-Route-Recommendation Algorithm Based on the Improved AGNES Spatial Clustering and Space-Time Deduction Model

Tour-Route-Recommendation Algorithm Based on the Improved AGNES Spatial Clustering and Space-Time Deduction Model

Towards developing a cyber-physical warehouse system for automated order-picking for online shopping

A Novel Urban Tourism Path Planning Approach Based on a Multiobjective Genetic Algorithm

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