Dial-a-ride problems consist of designing vehicle routes and time schedules in a system of demand-dependent, collective people transportation. In the standard problem, operational costs are minimized, subject to full demand satisfaction and service level requirements. However, to enhance the practical applicability of solution methods, authors increasingly focus on problem variants that adopt additional real-life characteristics. First, this work introduces an up-to-date classification that distinguishes multiple categories of real-life characteristics. Second, the wide range of solution methods proposed in the literature is reviewed in a structured manner. Although the existing literature is reviewed exhaustively, specific attention is devoted to recent developments. Third, an extensive overview table provides full details on all problem characteristics and solution methods applied in each paper discussed. Fourth, lacunae in research conducted to date and opportunities for future work are identified. Keywords dial-a-ride • demand-responsive transportation • patient transportation • rich vehicle routing • real-life characteristics • literature review
Dial-a-ride services provide collective on-demand transportation, usually tailored to the needs of people with reduced mobility. This paper investigates the operational effects of horizontal cooperation among diala-ride providers. The current practice is that users choose a particular provider to submit their requests. Providers operating in the same area create their routing solutions independently of each other, given their own set of customers. In contrast, horizontal cooperation through joint route planning implies that customer requests can be exchanged among providers in order to minimize the overall routing cost. In addition to quantifying the operational benefits generated by such a horizontal cooperation, this paper identifies operational characteristics that influence the magnitude of the savings. A real-life case study reveals the reasons why providers benefit from certain request exchanges, as well as the extent to which these exchanges are predictable in advance. The solutions are obtained using a large neighborhood search algorithm that performs well on benchmark data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.