Joint optimisation of regular and demand-responsive transit services

Zhao, Jing; Sun, Sicheng; Cats, Oded

doi:10.1080/23249935.2021.1987580

Cited by 24 publications

(13 citation statements)

References 44 publications

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“…As expected, heuristics are widely applied thanks to their capability to tackle real‐world instances, with multiple examples of GAs (Wang et al., 2020b; Wei et al., 2020; Wang et al., 2020a; Zhao et al., 2021), LS (Galarza Montenegro et al., 2021; Wu et al., 2022a), and ad hoc heuristics (Stiglic et al., 2018; Kumar and Khani, 2021; Yang et al., 2022).…”

Section: Towards An Integration Of Fixed and Flexible Transport Servicesmentioning

confidence: 96%

Trends in passenger transport optimisation

Filippi

Guastaroba

Peirano

et al. 2023

Int Trans Operational Res

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The growing number and complexity of modern megalopolises, where several millions of inhabitants request efficient transport services, pose colossal challenges to urban mobility. To capture the ever‐increasing demand for mobility without further deteriorating the traffic congestion, it is essential that the resources available are used as efficiently as possible. Besides, the traditional means of transport (train, metro, bus, taxi), each responds to a particular segment of the global demand for mobility. Nowadays, transport planners can take advantage of the progress in information technologies and optimisation methods to design modern services that integrate and coordinate different means of transport. These services are potentially capable of capturing additional segments of mobility demand and, as an outcome, reduce the usage of private vehicles. Building upon these general ideas, a growing number of researchers have studied various forms of transport flexibility as well as the integration among different means of transport. This survey provides an overview of the trends emerging from contributions from the operational research literature on urban passenger transportation. We have analysed the literature according to the dimensions of flexibility and integration of the transport service studied. For each of the application areas identified, we convey the main trends studied, summarise the most relevant solution approaches and outline some open research directions that deserve particular attention.

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Section: Towards An Integration Of Fixed and Flexible Transport Servicesmentioning

confidence: 96%

Trends in passenger transport optimisation

Filippi

Guastaroba

Peirano

et al. 2023

Int Trans Operational Res

View full text Add to dashboard Cite

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“…The benefit associated is specific to the operators' intent like increasing revenue/fare income [9], reducing parking infrastructure investment [17], increasing mobility, reducing vehicle miles and emissions, or replacing a costly transit alternative DRT/FBT for paratransit passengers and passengers in suburban or rural areas [8]. The design of SFT includes constraints characteristic of regular bus transit design including capacity [11], vehicle arrival and departure schedule [9], travel time [8], and fleet size [19] in addition to including constraints characteristic of DRT like zoning [10] and passenger pick-up and drop-off schedule [9]. Finally, for a given set of objective functions and constraints, the optimal value of decision variables can be derived using analytical models [11], numerical approximation [20], simulation [8], and heuristics [21].…”

Section: A Key Elements Of Flexible Transit Service Designmentioning

confidence: 99%

Optimal Design of Integrated Semi-Flexible Transit Services in Low-Demand Conditions

Mishra

Mehran

2023

IEEE Access

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Semi-flexible transit (SFT) is commonly discussed as a cost-effective alternative to serving public transportation users in low-demand conditions. We hypothesize that joint optimization of service headway and slack time per trip for route deviation is essential for designing a schedule for the operation of an integrated SFT that can meet both fixed-route and paratransit demand. An integrated SFT has the potential to lower the cost of transportation for regular transit users (both operators and riders) while redirecting potential paratransit riders to less expensive transit modes; thus, reducing demand for overwhelmed paratransit services operating with limited resources. The optimization problem has three competing objectives: minimizing operator costs, minimizing user costs, and maximizing service benefits. Two state-ofthe-art multi-objective evolutionary algorithms NSGA-II and SMPSO are compared to obtain the most representative deterministic Pareto optimal solution set. This study has three major contributions. First, quantile regression is used to suggest multiple slack time values for a given headway that transit planners can consider when generating a static schedule for SFT operation. Second, relationships derived to analyze cost trade-offs suggest that headway governs operator cost and is negatively correlated, user cost is positively and equally influenced by both variables, and slack time governs service benefit and is positively correlated. Third, sensitivity analysis for an integrated SFT operation reveals that low-capacity minivans and standard vans offer higher vehicle occupancy and cost efficiency, mostly economical for low to medium demand (5-20 pass/hr), low permissible deviation from the fixed route is desirable during peak hours to avoid delays for passengers on-board, and extreme weather conditions dramatically and negatively influence costs. Policy recommendations for integrated SFT implementation include a recommendation for fare structure design addressing service equity through surcharges/discounts, vehicle technology and service booking technology advancements for cost reduction, and fleet mix design through estimation of passenger loading profile. The application of the study methodology is demonstrated for a low-demand bus route in Regina, Canada.

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“…Last several years, a particle swarm optimization algorithm has been proposed to explore the efficient solution of UTRP [38]. Zhao et al [43] proposed a network optimization model that considered regular and demand-responsive transit services jointly and used a tailored boundary-start-based two-step heuristic algorithm to solve the model. Sachan and Mathew [44] proposed an integrated multimodal transit network design model and used a genetic algorithm to solve the proposed model.…”

Section: Urban Transit Routing Problem (Utrp)mentioning

confidence: 99%

Optimal design method of public transit network considering transfer efficiency

Jing

Yao

Chen

et al. 2023

IET Intelligent Trans Sys

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Improving the sharing rate of public transport and reducing operation costs are key factors affecting the sustainable development of the public transport system. After quantifying the impact of transfer, this study proposes a multi‐objective optimization model of bus networks considering the integral transfer efficiency and operation costs, whose optimal solution is hard to find. Since the heuristic algorithm has great global searchability, a non‐dominated sorted genetic algorithm (NSGA‐II) is adopted to solve this NP‐hard problem. Also, an adaptive mutation mode selection algorithm is proposed to enhance the solution efficiency. The optimization framework is applied to the benchmark case of the Swiss public transit network. The results show that the method significantly improves the transfer efficiency of the designed network when compared to existing studies. After calculation, it is found that enhancing the direct rate can improve transfer efficiency, but with high costs. Moreover, the proposed method can design an efficient and economic network to balance the benefits of passengers and operators in practice.

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Joint optimisation of regular and demand-responsive transit services

Cited by 24 publications

References 44 publications

Trends in passenger transport optimisation

Trends in passenger transport optimisation

Optimal Design of Integrated Semi-Flexible Transit Services in Low-Demand Conditions

Optimal design method of public transit network considering transfer efficiency

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