JUG Milano Meeting #160
Martedì 10 Dicembre 2024
The Art of Café Scheduling with the PlanningAI Timefold in Java: No more spilled shifts!
L'incontro si terrà Martedì 10 Dicembre 2024 presso eDream ODIGEO Via Fara 26 20124 Milano - evento gratuito previa registrazione OBBLIGATORIA (vedi dettagli) (mappa) in Via Gustavo Fara, 26, 20124 Milano MI For this event, we collaborated with Tech Talks by eDreams ODIGEO, a series of free conferences dedicated to showing the use of disruptive technology in the transformation of travel.
eDreams ODIGEO, is the world’s leading travel subscription platform and one of the largest e-commerce businesses in Europe. Tech Talks happens in 6 locations across 3 countries, where the eDreams ODIGEO Tech Labs are based: Madrid, Mallorca, Alicante, Milan and Porto. .
Evento ibrido online ed in presenza.
La partecipazione **in presenza** è gratuita e libera, ma è OBBLIGATORIA la registrazione su: form di registrazione per partecipare a JUG Milano in presenza
La partecipazione **in presenza** è gratuita e libera, ma è OBBLIGATORIA la registrazione su: form di registrazione per partecipare a JUG Milano in presenza
Abstract dell'intervento:
The world is full of complex planning challenges – whether in construction projects, production, vehicle routing, or, to make it more relatable, in scheduling shifts for employees in a busy café in Milan.
Imagine a café where you need to balance employee availability and skills with the demands of the business every day. Who can cover the morning or evening shifts? Who has the necessary barista skills? And how do you ensure no one works overtime or violates labor regulations?
To solve such challenges, Timefold offers a proven, powerful open-source solution in Java. With Timefold, complex planning problems – like our café scheduling – can be easily modeled using POJOs, annotations, and a Stream API.
In my talk, I will first explain when this solution is particularly useful and how PlanningAI differs from GenAI. Then, step by step, I'll demonstrate how to model and optimize our café’s shift scheduling problem using Timefold. Finally, I’ll show how to integrate it with Quarkus as a cloud-native application, enabling developers to build planning systems directly in Java.
The world is full of complex planning challenges – whether in construction projects, production, vehicle routing, or, to make it more relatable, in scheduling shifts for employees in a busy café in Milan.
Imagine a café where you need to balance employee availability and skills with the demands of the business every day. Who can cover the morning or evening shifts? Who has the necessary barista skills? And how do you ensure no one works overtime or violates labor regulations?
To solve such challenges, Timefold offers a proven, powerful open-source solution in Java. With Timefold, complex planning problems – like our café scheduling – can be easily modeled using POJOs, annotations, and a Stream API.
In my talk, I will first explain when this solution is particularly useful and how PlanningAI differs from GenAI. Then, step by step, I'll demonstrate how to model and optimize our café’s shift scheduling problem using Timefold. Finally, I’ll show how to integrate it with Quarkus as a cloud-native application, enabling developers to build planning systems directly in Java.
A cura di Simon Tiffert:
Simon is the Managing Director of OptaZEN GmbH and has been part of the agile Java ecosystem for over 20 years, taking on various roles throughout his career.
With more than a decade of experience working with Timefold and its predecessors, he combines his background in Java development with insights gained from his studies in scientific programming.
Simon has a keen interest in solving complex planning problems and exploring how PlanningAI-driven solutions can address real-world challenges.
Simon is the Managing Director of OptaZEN GmbH and has been part of the agile Java ecosystem for over 20 years, taking on various roles throughout his career.
With more than a decade of experience working with Timefold and its predecessors, he combines his background in Java development with insights gained from his studies in scientific programming.
Simon has a keen interest in solving complex planning problems and exploring how PlanningAI-driven solutions can address real-world challenges.