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Geoffrey De Smet
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Geoffrey De Smet

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OptaPlanner 6.3 will support bi-directional variables for non-chained planning variables too. If A points to B, then B points to A. Even as planning variables get modified during planning, that principle stays true.
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I is balance of easy use and memory use as such facts are cloned I suppose.
What we could in the current version is to have ComputerAssignment entity which points a computer and has a processList, will it be done inside Planner?
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New Blog: Visualizing an #OptaPlanner Vehicle Routing solution with Leaflet (OpenStreetMaps) and Google Maps
http://www.optaplanner.org/blog/2015/03/10/VisualizingVehicleRoutingWithLeafletAndGoogleMaps.html
After OptaPlanner finds the best solution for a Vehicle Routing Problem, users usually want to see it on a real map, such as Google Maps or OpenStreetMap. The optaplanner-webexamples.war for OptaPlanner 6.3 now demonstrates that. Visualization In the case below, I’ve solved a VRP problem with 50 locations and 8 vehicles and projected the best...
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Geoffrey De Smet

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Finally out the door :) Enjoy!
 
OptaPlanner 6.2.0.Final released!
- Giant leap for the Vehicle Routing Problem (Nearby Selection, TailChainSwapMove, shadow variable efficiency)
- Strategic Oscillation Tabu Search
- New example: Cheap time scheduling
- New benchmarker statistics
- and more
http://www.optaplanner.org/download/releaseNotes/releaseNotes6.2.html
New and noteworthy, demo's and status for OptaPlanner 6.2.
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Geoffrey De Smet

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How fast is logging in #java?
What's the impact of logging levels and console/file appenders?
What’s the cost of trace/debug logging in production? What’s the performance cost of logging to a file? In these benchmarks, I compare the performance impact of logging levels (error, warn, info, debug, trace) and logging appenders (console appender, file appender) on several realistic OptaPlanner use cases. Benchmark methodology Logging implementation: SFL4J 1.7.2 with Logback 1.0.9...
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Demo video of new example in #OptaPlanner : Cheap Time Scheduling to reduce power costs.
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JBoss Community Asylum, a podcast about, for and by The JBoss Community
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Have him in circles
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3 Bugs in The Ultimate American Road Trip of The Washington Post
http://www.optaplanner.org/blog/2015/03/20/3BugsInTheUltimateAmericanRoadTrip.html
Earlier this week, The Washington Post published an article about how a data genius has computed the ultimate American road trip. The only problem…​ it contains several mistakes! It’s not the optimal route, nor the shortest route, nor the fastest route. Let’s take a look at the problems and how we can fix...
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I'll do an OptaPlanner webinar with Q&A this Wednesday, register now:
https://vts.inxpo.com/Launch/QReg.htm?ShowKey=24231&AffiliateData=socialmedia
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Java's reputation is still for sale...
 
Mac OS X users no longer safe from the Java Ask add-on of doom. Internet responds with disappointment/snark. http://buff.ly/1E1sp9H
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Sizing OptaPlanner / Business Resource Planner
 
A sneak peak at sizing Business Resource Planner.
(Article guest authored together with Maggie Hu, Senior Middleware Solutions Architect at Red Hat in North America and Geoffrey de Smet, Senior Software Engineer at Red Hat in Europe) Two of the biggest questions anyone has w...
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Scaling the Vehicle Routing Problem above 1000 customers with Nearby Selection in OptaPlanner 6.2.
#orms #vrp #OptaPlanner
OptaPlanner 6.2 has made big step forward for the Vehicle Routing Problem (VRP), Traveling Salesman Problem (TSP) and similar use cases. The new feature nearby selection enables it to scale to bigger problems much more efficiently without sacrificing potential optimal solutions (which is common for inferior techniques). Let’s take a closer look at nearby...
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Understanding natural language, neural nets by example. Fascinating.
 
Understanding Deep Neural Networks

Over the last few years, Deep Neural Networks (DNNs) have been increasingly used in various applications, from speech recognition (http://goo.gl/vVVCPT) to computer vision and image classification (http://goo.gl/1pNzn4). 

But what exactly are DNNs, and how do they work?

Former Google intern +Christopher Olah has written a blog post that uses dimensionality reduction and interactive visualizations to help understand what exactly is happening “under the hood”, giving one an intuition on the internal operations of DNNs.
In a previous post, we explored techniques for visualizing high-dimensional data. Trying to visualize high dimensional data is, by itself, very interesting, but my real goal is something else. I think these techniques form a set of basic building blocks to try and understand machine learning, ...
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Have him in circles
891 people
Bulent Soykan's profile photo
Muhammad Arif Kamal's profile photo
Carleton Coffrin's profile photo
Carlos Pérez Ortega's profile photo
Hugo Guerrero's profile photo
Mark Proctor's profile photo
Jesper Jørgensen's profile photo
jeroen defour's profile photo
Marianne Dupres's profile photo
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OptaPlanner lead
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OptaPlanner lead
Introduction
I am the lead for OptaPlanner (java, open source) and I work for Red Hat.


OptaPlanner optimizes business resource usage. Every organization faces planning problems: provide products or services with a limited set of constrained resources (employees, assets, time and money). OptaPlanner optimizes such planning to do more business with less resources.

OptaPlanner is a lightweight, embeddable planning engine written in Java™. It helps normal Java™ programmers solve constraint satisfaction problems efficiently. Under the hood, it combines optimization heuristics and metaheuristics with very efficient score calculation.

OptaPlanner is open source software, released under the Apache Software License. It is 100% pure Java™, runs on any JVM and is available in the Maven Central Repository too.

For more information, visit http://www.optaplanner.org
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