Decision support system for collaborative freight transportation management

A tool for mixing traditional and green logisticsProf. Guido Perboli

guido.perboli@polito.it

Agenda

An overview of the collaborative transportation Case study: the City of Turin Decision Support System Results

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An overview of the collaborative transportation I

In the recent years, Collaborative Strategies are introduced in theurban freight transportation system.

The aim of this collaboration is fourfold: Improve the value-chain efficiency and effectiveness Reduce the overall costs Harmonize data analysis Environmental sustainability

But considering an important constraint: Not compromising theCompetitive Advantage of firms involved.

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An overview of the collaborative transportation II

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Companies overcome the idea of a trade-off between: The economical efficiency and effectiveness of transportation

activities The environmental impact

Green solution as source of competitive advantage.

Collaborative transportation: the case study I

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Case study of collaborative transportation in the City of Turin (Italy): Last Mile segment

Two couriers involved: Big Parcel Delivery (BPD) company (TNT, DHL, SDA) Cargo bike courier - Pony Zero S.r.l.

Freight Pooling With hierarchical decision-making

Collaborative transportation: the case study II

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Pony Zero deliveries are assigned to each biker following a proprietary algorithm.

The algorithm calculates the best possible route for each biker, optimizing their delivery route, the time,

distances travelled and prioritizing specific time slots

The biker is able to check any delivery details utilizing an App on his smartphone at any time.He can view a real time map in order to navigate and report to center manager any potential delivery issue that may occur.

SUSTAINABLEURBAN LOGISTICS

Collaborative transportation: the case study III

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From Pony Zero S.r.l. to BPD Pony Zero S.r.l. offers to the BPD a value proposition consisting

in the urban green logistics services using bikes and cargobikes. Costs and efficiency optimization Overcome of complexities in urban areas (e.g., parking issues, LTZ

areas, …) Green image and green credentials

Collaborative transportation: the case study IV

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From BPD to Pony Zero S.r.l. At the same time, Pony Zero S.r.l. obtains the critical mass to

sustain its business model

Multi-Actor and Multi-Modal system

Need of a Decision Support System to automatize and optimizethe entire operative and decision processes.

Decision Support System I

The DSS has been developed by the ICE Laboratory (ICT for CityLogistics and Enterprises) of the DAUIN – Politecnico di Torinoand the Istituto Superiore Mario Boella and under the supervision ofprof. Guido Perboli

The DSS provides the planning of fleet usage and routes, and theoptimization of the total delivery time and the traveled distancesconsidering: the balancing of the routes constraints related to the bikes green aspect

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Decision Support System II

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OPTIMIZATION ALGORITHMLarge Neighborhood SearchOptimize the planning of routes anddispatchers

DECISION SUPPORT SYSTEM

ERP “ODOO”Database server “PostgreSQL”Application serverJavaScript application

Decision Support System III

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CLIENT IMPORTCLIENT MANAGEMENT

TRIP CREATION

TRIP MANAGEMENTLOADING

DELIVERY

Decision Support System IV

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Results I

Operative results. Combining the DSS with the green vehicle per excellence as the bike, Pony Zero S.r.l. obtains: Reduction of the delivery time Increase of the quality level perceived by the customers Increase of the competitive advantage Limitation of the business model repeatability

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Results II

Environmental results. Measured by means of a simulation analysis. Higher reduction of CO2 emissions when bikers manage parcels

with a weight up to 5 kg.

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Instances Number of parcelweight served by the green courier

CO2 savings per day[kg]

Δ Distance traveled by traditional courier

[%]

Deliveries per hour for green courier

[%] Semi-Centre Centre Semi-Centre Centre Semi-Centre CentreInstance 1 0-3 kg 33.68 21.69 - 22% - 24% 71.83% 76.40% Instance 2 0-3 kg 33.86 15.63 - 18% - 15% 70.17% 73.59%Instance 3 0-3 kg 40.91 25.61 - 22% - 17% 72.14% 74.00%Instance 1 0-3 kg and 3-5 kg 45.24 26.89 - 29% - 30% 76.32% 79.80%Instance 2 0-3 kg and 3-5 kg 43.95 25.53 - 24% - 24% 74.52% 76.54%Instance 3 0-3 kg and 3-5 kg 47.88 19.71 - 26% - 21% 77.84% 78.68%

Results III

Technologic-based results. Steep initial learning curve, due to the lack of documentation

concerning the Odoo version 8.0 Customizable, lean and efficient Reduction of the ICT maintenance costs for Pony Zero S.r.l. due

to the cloud-base deployment

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