fleet management and optimisation - industrial placement presentation
TRANSCRIPT
Lorenzo Paoliani Industrial Placement 2016MEng Computing | Imperial College London
Fleet Management and Optimisationcode that delivers
Pie is a solution for logistics and transportation companies to manage their
vehicles and power their operations.
PLANNING TRACKING ROUTING
Manage drivers and fleet
Register customer orders
Track vehicles on the roadApp for drivers
Route vehicles from A to B
Route around restrictions for large vehicles, road
closures, etc.
Over the course of my placement I focused on 3 areas
UI UX DXUser
InterfaceUser
ExperienceDeveloper Experience
Storybook• Separates “pure” view components from
the main app • Allows to describe the intent behind a
component by describing a story of its possible rendering states
• Distraction free environment • Quickly iterate • Communicate with the design team • Track use cases, error and loading states
Filters• Logic and UI to filter deeply nested data • Filters pile on top of each other • Recursively descends into an entity
checking whether the current piece of information is hidden or visible
• At every level, after visiting the children nodes, the parent decides its status
• This allows to mark every node as one of VISIBLE / DISABLED / HIDDEN
The Problem
• 100+ locations to dispatch vehicles • Thousands of vehicles • Pick up freight from 300+ locations all over the UK every day • Sort the deliveries and send them towards the right regional
depot • Must arrange a plan to fulfil all the orders
The Problem• 130+ locations to dispatch vehicles • Thousands of vehicles • Pick up freight from 300+ locations all over the UK every day • Sort the deliveries and send them towards the right regional
depot • Must arrange a plan to fulfil all the orders
Right now, this is done in an office, by hand, every day.
based on a 2011 paper:An Iterated Local Search heuristic for the Heterogeneous Fleet Vehicle Routing Problem• Defines the HFVRP and its subcategories • 2 hard problems in computer science
• Travelling Salesman Problem • Bin Packing Problem
• Searches solutions iteratively through a small subset of similar solutions from the solution space
• Uses random perturbation of candidate solutions to escape local minima
• Any solution - even no optimisation! - is better than the current state of the long haul logistics
Penna, P.H.V., Subramanian, A. & Ochi, L.S. J Heuristics (2013) 19: 201. doi:10.1007/s10732-011-9186-y
API + Solver• Exposes an API to build and solve a
Heterogeneous Fleet Vehicle Routing Problem
• Input: a set of dispatching locations and a set of pickup jobs
• Output: a fulfilment plan that connects jobs and dispatchers
• Handles pickup time, service time, volume, and weight constraints
• Selects best vehicle type to service a route
Technology
graphhopper/jspritan open source implementation of the algorithms described in
the HFVRP paper
Statically typed programming language
for the JVM
Engine App
Lorenzo Paoliani [email protected]
Industrial Placement 2016MEng Computing | Imperial College London
Thanks!