Shared parking for ride-sourcing platforms to reduce cruising traffic

Gao, Jing Ru; Li, Sen; Yang, Hai

doi:10.1016/j.trc.2022.103562

Cited by 26 publications

(8 citation statements)

References 28 publications

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“…In recent years, the concepts of collaboration and sharing have been introduced in many studies to realize the efficient configuration of resources, thereby promoting cost and resource savings through multidepot collaboration [48][49][50]. Many third-party platforms are created to provide sharing services, which promote various collaboration modes [51,52]. Wei et al [53] investigated a matching problem for ride-sourcing markets.…”

Section: Cmvrpdcdtwmentioning

confidence: 99%

Collaborative Multidepot Vehicle Routing Problem with Dynamic Customer Demands and Time Windows

et al. 2022

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Dynamic customer demands impose new challenges for vehicle routing optimization with time windows, in which customer demands appear dynamically within the working periods of depots. The delivery routes should be adjusted for the new customer demands as soon as possible when new customer demands emerge. This study investigates a collaborative multidepot vehicle routing problem with dynamic customer demands and time windows (CMVRPDCDTW) by considering resource sharing and dynamic customer demands. Resource sharing of multidepot across multiple service periods can maximize logistics resource utilization and improve the operating efficiency of delivery logistics networks. A bi-objective optimization model is constructed to optimize the vehicle routes while minimizing the total operating cost and number of vehicles. A hybrid algorithm composed of the improved k-medoids clustering algorithm and improved multiobjective particle swarm optimization based on the dynamic insertion strategy (IMOPSO-DIS) algorithm is designed to find near-optimal solutions for the proposed problem. The improved k-medoids clustering algorithm assigns customers to depots in terms of specific distances to obtain the clustering units, whereas the IMOPSO-DIS algorithm optimizes vehicle routes for each clustering unit by updating the external archive. The elite learning strategy and dynamic insertion strategy are applied to maintain the diversity of the swarm and enhance the search ability in the dynamic environment. The experiment results with 26 instances show that the performance of IMOPSO-DIS is superior to the performance of multiobjective particle swarm optimization, nondominated sorting genetic algorithm-II, and multiobjective evolutionary algorithm. A case study in Chongqing City, China is implemented, and the related results are analyzed. This study provides efficient optimization strategies to solve CMVRPDCDTW. The results reveal a 32.5% reduction in total operating costs and savings of 29 delivery vehicles after optimization. It can also improve the intelligence level of the distribution logistics network, promote the sustainable development of urban logistics and transportation systems, and has meaningful implications for enterprises and government to provide theoretical and decision supports in economic and social development.

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Section: Cmvrpdcdtwmentioning

confidence: 99%

Collaborative Multidepot Vehicle Routing Problem with Dynamic Customer Demands and Time Windows

et al. 2022

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“…The operation and management of curbside spaces originate from practical needs. On-street parking in downtown area is a fundamental function of curb spaces and has been studied extensively such as cruising behavior (Geroliminis, 2015;Zheng and Geroliminis, 2016), impact on congestion (Arnott andInci, 2006, 2010) and dynamic pricing strategies (Qian and Rajagopal, 2014;Pu et al, 2017;Lei and Ouyang, 2017), but few of them considered curb usage of different participants together. Caleb et al (2021) made a comprehensive review of existing pilot projects of curbside usage and policies, summarizing incoming challenges, demands and opportunities.…”

Section: Curb Operation and Managementmentioning

confidence: 99%

“…Operations of ride-hailing services have also been studied intensively including location prediction of the next rider pickup (Nair et al, 2020), service matching (Qin et al, 2021) and vehicle rebalancing (Kontou et al, 2020;Guo et al, 2021;Zhu et al, 2022), demand prediction (Battifarano and Qian, 2019), ride reservations (Yahia et al, 2021), impact of expanding service (Beojone and Geroliminis, 2021), shared parking (Gao et al, 2022), and management strategies such as pricing for related parking infrastructure (Liu et al, 2021), service platform and market (Zha et al, 2016;Nourinejad and Ramezani, 2020). A macroscopic fluid framework for operating a large-scale on-demand ride-hailing system was developed and used for decision making (Xu et al, 2021).…”

Section: Ride-hailing Servicesmentioning

confidence: 99%

Optimal Curbside Pricing for Managing Ride-Hailing Pick-Ups and Drop-Offs

Liu

Qian

2022

SSRN Journal

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“…Achieving optimal company performance can be achieved if every organization, both the private sector and the public sector, has a competitive advantage. (Gao et al, 2022) explains that competitive advantage can be formed in various ways, such as creating products with unique designs, using modern technology, organizational designs, and using existing resources effectively, efficiently and economically. In line with what was revealed (Kim et al, 2021) competitive advantage can be realized in terms of gaining strategic, tactical and operational advantages.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Intellectual Capital on Financial Company: Empirical Study from Indonesia

Sutisna,

Pasolo,

Sutisman

et al. 2023

daengku j. hum. soc. sci. innov.

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This study examines: 1) The Effect of Value-Added Capital Employed (VACA) on Financial Performance. 2) Effect of value-added human capital (VAHU) on financial performance 3) Effect of Structural Capital Value Added (STVA) on Financial Performance. The population of this study is manufacturing companies listed on the Indonesia Stock Exchange from 2018 to 2022. The number of companies studied was 41. The sampling technique used was purposive. The type of sample is obtained based on predetermined criteria. The data used is quantitative data obtained in the form of numbers that can be calculated by accessing the IDX.co.id site and the official website of each company. The data analysis technique used is multiple regression analysis. The study results show that: 1) Value Added Capital Employed (VACA) positively and significantly affects financial performance. 2) Value-added human capital (VAHU) has a positive and insignificant effect on financial performance. 3) Structural Capital Value Added (STVA) positively and significantly affects financial performance.

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Shared parking for ride-sourcing platforms to reduce cruising traffic

Cited by 26 publications

References 28 publications

Collaborative Multidepot Vehicle Routing Problem with Dynamic Customer Demands and Time Windows

Collaborative Multidepot Vehicle Routing Problem with Dynamic Customer Demands and Time Windows

Optimal Curbside Pricing for Managing Ride-Hailing Pick-Ups and Drop-Offs

The Effect of Intellectual Capital on Financial Company: Empirical Study from Indonesia

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