Logistic network optimization and scheduling
Project Idea Metadata
- Project Idea Name: Logistic network optimization and scheduling
- Date: 3/8/2023 7:17:11 PM
- Administrators:
Project Idea Description
Project idea description
What problem would you like to solve?
Logistics networks in specific businesses often suffer from inefficient scheduling and routing practices.
These businesses face specific constraints that are not accommodated by the standard tools available in the market, hence they are not optimized.
For example, despite the complexity of managing a daily client visit schedule for home care networks, with ongoing projects covering over 40,000km per day for 36,000 clients, many organizations still rely on manual methods.
The specific requirements of these businesses, including for example the need to match clients with specific care needs to competent employees and the need to manage low expiration delays, make standard optimization tools designed for package delivery unsuitable. As a result, scheduling and optimization are often still done manually.
However, the increasing quantity and quality of data collection over the past decade have made it possible to develop tailor-made solutions that automate and optimize processes. The uniqueness of our approach consists of providing the customer with a tailor-made solution to automate and optimize the planning of their vehicle routes; resulting in better quality, less km traveled and less equipment required.
Results achieved in the past: 30% reduction in the number of instruments required for analysis, 30% reduction in the number of vehicles needed for transportation, 20% reduction in the number of km traveled each day.
The algorithm developped for this project have been published: Integrating Vehicle Routing and Resource Allocation in a Pharmaceutical Network – In: Advances in Optimization and Decision Science for Society, Services and Enterprises.
Who are the customers and how will they profit from a solution?
All companies and associations that operate an internal logistics network, having specific constraints and therefore not being able to use a standard tool (such as for postal deliveries). Customers with specific constraints could be:
- home-care network composed of multiple intervention types requiring specific competences, specific relationship with clients.
- Biological sample collection networks, with low expiration delays or a downstream load at analysis centers to be smoothed out
- Delivery networks for fruit & vegetable at home, with collection and delivery points varying continuously,
- Home cleaning networks, with variable cleaning frequency and duration.
The benefits are: less km, fewer vehicles and other resources, fewer costs, fewer delays, fewer wastes, more time with patients.
How does your project idea affect energy savings or CO2 emissions?
Our project focuses on optimizing vehicle networks that cover thousands of kilometers each day. By reducing the distance traveled and the number of vehicles or resources needed (gray energy), we can significantly decrease energy consumption and CO2 emissions. Furthermore, our solution ties the reduction of CO2 emissions directly to cost savings, providing an additional incentive for adoption.
Result of a project done in the past: 1'000 km per day saved, 31 tons of CO2 saved per year.
We are currently working on a project that has a potential saving of 248 tons of CO2 each year.
With our current capabilities (~ 3 projects/year), we estimate a potential cumulative saving of 20'000 tons over 10 years. If our team expands and communication around our solution is effective, the gains can be even greater.
In addition, reducing the number of km traveled frees up time. Thus, in the case where the service provider travels himself (e.g. home care), he spends more time using his skills rather than driving.
Finally, optimization allows better quality, by establishing reliable routes that limit errors and stress, or by better respecting certain specific planning criteria, such as favoring the same caregiver for a given patient.
Current status and previous activities
What has been tried before?
Our first project was developed during our previous professional experiences with a pharmaceutical network. The outcomes were significant, including:
- 50% reduction in late arrivals (critical when dealing with biological samples),
- 30% reduction in the instruments required for the analysis,
- 30% reduction in the number of vehicles needed for transportation,
- 20% reduction in the number of kilometers traveled daily (-1’000km/day – 31t-CO2-eq/year).
We are currently working with a home-care network located in the French part of Switzerland. Despite the complexity of managing a daily client visit schedule for home care networks, with ongoing projects covering over 40,000km per day for 36,000 clients, they still rely on manual methods. We expect here a potential saving of 248t-CO2-eq/year.
What was not successful?
The effort to gain a comprehensive understanding of our clients' processes, collect accurate data, and validate our comprehension takes more time than anticipated.
What have you learned?
As a result, we have revised our project timelines upwards. We have found that having an accurate understanding of our clients' processes and a solid grasp of the data is essential for building effective solutions. This is what sets our approach apart from 'black box' methods that may not provide the necessary level of understanding for the successful implementation.
Furthermore, we believe that this approach is highly pragmatic and effective for advancing the environmental cause. By demonstrating that these solutions deliver financial and organizational benefits while reducing CO2 emissions, we can make a strong case for their adoption.
Resources needed
What are your planned work packages?
We build customized solutions to optimize the scheduling and routing of logistics networks.
1. Consulting on site to collect real case data, specific business constraints and current organization of the network.
2. Developing a specific solution integrating the business-specific constraints
3. Validation of the solution and comparison to the benchmark (actual organization)
4. Delivery of the new planification and application.
We estimate that a typical project pays back 10 to 20 times what it costs within one year, based on previous results.
How can the Energy Lab help you?
The technical aspect of our solution is proven effective in a real-world business case.
However, we are currently encountering challenges in the commercialization phase. Cold emailing has not proven to be an effective method for reaching potential clients. In contrast, face-to-face meetings have resulted in more interest from clients and led to the initiation of new projects, such as with our current project.
Therefore, our main challenge is to effectively communicate the benefits of our solution, expand our network, and directly reach potential customers. To address this challenge, we propose the following actions:
1. Attend specific business conferences. (CHF 11’750)
a. Leaders in Logistics summit: 2 tickets CHF 5’000
https://marketforcelive.com/leaders-in-logistics/events/summit/
b. Supply Chain & Logistics conference: 2 tickets CHF 3’300
https://swiss-supplychain.com/
c. Swiss IT forum(s): stand CHF 2’450
https://www.swiss-it-forums.tech/fr/
d. 22ème GS1 Forum Suisse de Logistique : 2 tickets CHF 1’000
https://fl.gs1.events/fr/; https://fl.gs1.events/media/documents/Flyer_Forum_Suisse_de_Logistique_2022_dLNL8gf.pdf
2. Develop marketing strategy (CHF 3000.- + 500.- monthly)
a. Increase Linkedin visibility: professionnal LinkedIn communication and mailing campaigns (~ CHF 500 per month)
b. Develop marketing materials such as brochures, case studies, and whitepapers (~ CHF 3’000)
3. Get relevant leads with an external agency or by hiring a part-time commercial
a. Seventic (~ CHF 3’000 per month); strongly recommended by other startups.
b. Part-time commercial (20 days): (~ CHF 5’000 per month)
In addition, today we measure the environmental impact of our solution, by transforming the gain in traveled km in CO2 emission. But a better and more interesting evaluation could be made by integrating the gain in resources (reduction in vehicles, production machines, ... ).
The goal of the project is to build customized solutions to optimize the scheduling and routing for logistic networks.
This kind of optimization usually enables to reduce the number of kilometers of a fleet of vehicles by 20%-30%.
The uniqueness of our approach consists of providing a tailor-made, applicable, profitable solution (AI/metaheuristic) to optimize the planning of their vehicle routes
1 project done in the past: 1'000 km per day saved, -31 tons of CO2/year.
current project potential: -240 tons/year