Developing a resource allocation model for the Scottish patient transport service

Abstract

The Patient Transport Service is a vital component of many healthcare systems. However, increasing demand and constrained resources impose great challenges, especially in Scotland where there is a substantial remote and rural population. This case study describes the development of a decision support tool for strategic resource allocation decisions. The tool had to be relevant to management's practical needs including transparency to a range of stakeholders and a flexible speedy response to help management explore various operational and policy options. However, the tool also had to demonstrate rigour and identify an efficient allocation of resources. In response to these requirements, the decision support tool was constructed from simple models, verified in comparisons with more rigorous and sophisticated approaches, notably a Dial-a-Ride genetic algorithm and an open vehicle routing simulation. Using this tool, management were able to: identify a more rational, strategic allocation of resources; quantify the remote and rural effect; examine trade-offs between service level and resource requirements within various scenarios for future demand.

Shuttle bus service routing: A systematic literature review

“…Commercial Solvers [8]- [13], [22], [28]- [46] Constraint Programming [46] Genetic Algorithm [14]- [16], [47]- [56] Tabu Search Algorithm [17]- [20], [22], [39], [42], [57]- [60] Clark&Wright Savings Algorithm [33], [61], [62] Maximin [63] K-means [14], [63]- [65] Fuzzy C-means [63], [65] Competitive Learning [63] Ant Colony Algorithm (ACO) [27], [35], [63], [66], [67] Evolutionary Algorithm [28], [58], [68] Greedy Algorithm [25], [34], [57], [69]- [71] Simulated Annealing [19], [20], [31], [36], [41], [43] Local Search [15], [19],…”