MPTR: A Maximal-Marginal-Relevance-Based Personalized Trip Recommendation Method

Luan, Wenjing; Liu, Guanjun; Jiang, Changjun; Zhou, MengChu

doi:10.1109/tits.2017.2781138

Cited by 36 publications

(21 citation statements)

References 32 publications

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“…Nevertheless, it would be too expensive and time-consuming to collect such run-time data in practice. Consequently, we consider introducing a large-scale-sparse-matrices-analysis model [47]- [50] to predict QoS of services, especially when historical QoS data is insufficient; and 3) we will try to use some recently proposed intelligent optimisation methods [51]- [55] and other methods [56], [57] for the considered problem.…”

Section: Discussionmentioning

confidence: 99%

Predictive-Trend-Aware Composition of Web Services With Time-Varying Quality-of-Service

et al. 2020

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Service composition is a technology capable of combing a collection of existing services where many smaller services are coordinated together to form a larger one. Functionally similar services can often show different quality-of-service (QoS) properties. For a specific service composition request, how to choose from a bag of suitable services that fulfill the required functions under given quality-ofservice constraints is widely believed to be a great challenge. The traditional approach usually tackles this problem by assuming fixed, bounded, or statistic QoS and views the decision-making of service composition as a static process. Instead, we address this problem by considering time-varying and fluctuating QoS and presenting a predictive-trend-aware service composition method by using a time series prediction model and genetic algorithms. We conduct extensive case studies based on multiple randomly-generated service templates with varying process configurations and show that our method outperforms existing ones. INDEX TERMS Time series, Quality-of-Service (QoS), service composition, genetic algorithm (GA).

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Section: Discussionmentioning

confidence: 99%

Predictive-Trend-Aware Composition of Web Services With Time-Varying Quality-of-Service

et al. 2020

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“…It would be of future interest to investigate the heterogeneous IoT system with underwater acoustic sensors. Furthermore, some location-based recommendation methods (e.g., [41], [42]) may be considered to be incorporated with the proposed approach in the future.…”

Section: Discussionmentioning

confidence: 99%

Three-Dimensional Internet-of-Things Deployment With Optimal Management Service Benefits for Smart Tourism Services in Forest Recreation Parks

Lin

Liu

2019

IEEE Access

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In a large-scale national forest recreation park, it is difficult for park managers to maintain facilities and provide timely or emergency services to visitors in need (e.g., elderly adults, children, or lost visitors without communication devices). To implement smart tourism services, park managers have introduced the Internet of things (IoT) to their parks, which has enabled the provision of diversified intelligent information services. However, most of the previous studies focused on 2D deployment of the IoT system to cover all targets, ignoring actual 3D topographic differences; their objectives rarely included the effectiveness of services generated from introducing the IoT; they assumed targets to be equally crucial, regardless of differences in tourism attractiveness (e.g., tourist attractions, view trails, and recreation facilities). Therefore, this study investigates 3D deployment of an IoT system to cover targets with different scores based on tourism attractiveness in a forest recreation park with optimal management service benefits, represented as a weighted sum of service quality index (SQI) and managerial setting attributes index (MSAI), so that the system collects the data from visitors equipped with wearable devices, and applies it to tasks such as physiological detection and positioning. This problem belongs to deployment and coverage problems, which have been shown to be NP-hard, and thus is also NP-hard. Therefore, this study further solves this problem by improved simulated annealing (ISA), including three neighborhood searching operators and the dynamic probability adjustment scheme. Experimental results under various parameter settings indicate that ISA has an excellent optimization ability.INDEX TERMS Smart tourism service, Internet of Things, simulated annealing, three-dimensional deployment, national forest recreation park.

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“…Besides, there are also some other algorithms that can inspire some ideas on solving MTSP [26]- [27]. In [28], Ting Huang et al propose a niching memetic algorithm for Multisolution Traveling Salesman Problem.…”

Section: B Related Work Applying Aco To Tsp and Mtspmentioning

confidence: 99%

Ant Colony Optimization With an Improved Pheromone Model for Solving MTSP With Capacity and Time Window Constraint

Wang

Ma²,

et al. 2020

IEEE Access

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The optimization of logistics distribution can be defined as the multiple traveling salesman problem (MTSP). The purpose of existing heuristic algorithms, such as Genetic Algorithm (GA), Ant Colony Algorithm (ACO), etc., is to find the optimal path in a short time. However, two important factors of logistics distribution optimization, including work time window and the carrying capacity of the vehicle in distribution system, have been ignored. In this paper, we consider the influences of time limitation of modern commercial logistics and carrying capacity of the vehicle on the logistics optimization, and then propose a MTSP with constraints of time window and capacity of each salesman. We design a novel hybrid algorithm by combining the minimum spanning 1-tree with ACO to find the optimal solution. In addition, we improve the pheromone update rules to increase the search efficiency of ACO algorithm. The experiments show that the novel hybrid algorithm achieves a shorter path than the other algorithms. INDEX TERMS multiple traveling salesman problem, ant colony optimization, time window, capacity

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MPTR: A Maximal-Marginal-Relevance-Based Personalized Trip Recommendation Method

Cited by 36 publications

References 32 publications

Predictive-Trend-Aware Composition of Web Services With Time-Varying Quality-of-Service

Predictive-Trend-Aware Composition of Web Services With Time-Varying Quality-of-Service

Three-Dimensional Internet-of-Things Deployment With Optimal Management Service Benefits for Smart Tourism Services in Forest Recreation Parks

Ant Colony Optimization With an Improved Pheromone Model for Solving MTSP With Capacity and Time Window Constraint

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