Dynamic dispatch algorithm proposal for last-mile delivery vehicle
| Autor: | Daniel de Oliveira Mota |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
education.field_of_study
General Computer Science Job shop scheduling Computer science business.industry Dynamic dispatch Population Context (language use) Cloud computing Scheduling (computing) Combinatorial optimization Probability distribution Electrical and Electronic Engineering education business Algorithm |
| Zdroj: | IEEE Latin America Transactions. 19:1618-1623 |
| ISSN: | 1548-0992 |
| Popis: | The complex urban scenario demands decisions which needs to be taken not only fast, but considering a high level of uncertainty. In such context, this study proposes an algorithm to address the vehicle allocation scheduling with a request list unknown a priori, and is revealed along the operation horizon. Based on the OSCO (online stochastic combinatorial optimization) problem, it is presented a framework to operate such problem in a last-mile delivery system where customers requests from e-commerce (or food delivery) along an operations day. The deterministic calculation was realized using a permutational flowshop scheduling problem with the objective of minimizing makespan. Experiments indicated convergence in the algorithm along the planning trials, and a satisfactory makespan prediction, before the orders are revealed, with accuracy. The probability distribution adheres with a bell-shaped (normal) distribution with its population parameters estimated using classical statistics inference theory. Incorporating uncertain in such type of mathematical modeling could open doors for a new era of systems in current days with cloud computing, big data, smart cities, and artificial intelligence. |
| Databáze: | OpenAIRE |
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