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An optimization-based approach is proposed for the joint design of fixed-route bus networks and the service areas of complementary paratransit services. Complementary paratransit systems provide transportation to people with disabilities within a service area (PSA) that is traditionally designed as a function of the spatial layout of a fixed-route bus network. The proposed problem accounts for effectiveness and equity objectives for the bus and paratransit services. A constraint on the minimum extension PSAs is considered, which is of practical interest given the coverage regulations faced by transit agencies in some jurisdictions. A two-step procedure is proposed to find solutions to the design problem. In the first step, bus route network designs are generated, along with their minimum PSAs. In the second step, a genetic algorithm improves upon the PSAs generated in the first step. Simulation tests were performed to illustrate the application of the proposed methodology. [ABSTRACT FROM AUTHOR]

In densely populated areas, ridepooling services are becoming more and more popular and can contribute to promote sustainable mobility concepts. In this paper, we study a dynamic dial-a-ride problem and propose a novel two-phase multiple plan approach. By maintaining multiple plans simultaneously over the course of the optimization procedure, we increase the likelihood and speed of a successful insertion for dynamically arising customer requests. Additionally, we present a new metric to replace the commonly used distance minimization as guidance within the optimization procedure. In order to examine the impact of certain instance characteristics on the quality of the solutions, we evaluate our design decisions on various instance sets. The results show that the proposed method consistently outperforms commonly used single plan approaches. [ABSTRACT FROM AUTHOR]

This paper investigates The Electric Vehicle Dial-a-Ride Problem: Integrating Ride-Sharing and Time-of-Use Electricity Pricing (DAR-RSTOU), which involves designing a set of minimum-cost routes to service all customers for a fleet of electric vehicles (EVs). The characteristics of the problem include: (1) the use of EVs and consideration of partial charging strategies; (2) a maximum ride time duration limit for each customer; (3) the possibility of ride-sharing among customers; (4) accounting for Time-of-Use (TOU) electricity pricing policies. We propose a novel mixed integer programming model to describe the problem, aiming to minimize the weighted sum of the charging, total travel, and detour penalty costs. Additionally, we have devised a customized adaptive large neighborhood search heuristic with an enhanced feasibility-checking method for rapid solution evaluation and dynamic programming to optimize the charging strategy for the fleet. Computational experiments on adapted benchmark instances from DARP literature and on instances based on real data from electric taxis in Shenzhen assess the validity of the DAR-RSTOU formulation and the heuristic algorithm. Parameter experiments highlight the algorithm's acceleration strategy effectiveness. Valuable managerial insights are derived from policy-oriented research on different electricity pricing strategies. • Propose a DARP extension considering ride sharing and TOU electricity pricing. • An arc flow model is introduced for this problem and subsequently linearized. • Design an ALNS algorithm for DAR-RSTOU with improved feasibility-checking techniques. • Integrate a dynamic programming algorithm for efficient problem-solving. • Gain valuable managerial insights from extensive experiments using real-world data. [ABSTRACT FROM AUTHOR]